Claude Opus 5 vs Claude Sonnet 5 Comparison

A step change at the Opus tier: the most durable model for long-running agentic tasks

VS
Claude Sonnet 5

Quality close to Opus 4.8, 2.5x cheaper — the default model for everyday workflows

17 min readAI

Quick Verdict

There's no clean single-model winner, but there is a clear rule: give specification-clear complex code, migrations, and hard verification work to Opus 5; leave discovery, file scanning, translation, and high-volume mechanical work to Sonnet 5. Don't reverse the order, either — Anthropic's official recommendation is to adjust effort before switching models. Try Sonnet 5 at high effort first; upgrade to Opus 5 only if the result isn't reliable or the task needs multi-turn self-verification.

Claude Opus 5Claude Sonnet 5
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Score Comparison

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Detailed Scoring

Detailed Scoring: Claude Opus 5 and Claude Sonnet 5 — category-by-category scores out of 10
CategoryClaude Opus 5Claude Sonnet 5
Performance
10/10
8/10
Ease of Learning
7/10
8/10
Ecosystem
8/10
8/10
Community
7/10
8/10
Job Market
8/10
9/10
Future-Proof
9/10
8/10

Pros & Cons

Claude Opus 5

Pros

  • Beats Opus 4.8's Frontier-Bench performance by more than 2x, at a lower cost
  • On CursorBench at max effort, trails Fable 5's peak score by only 0.5% — at half the cost
  • The default model on the Claude Max plan, and the strongest option on Claude Pro
  • Fast mode (research preview) can boost output speed by up to 2.5x
  • Knowledge cutoff of May 2026 — 4 months more recent than Sonnet 5
  • A significant improvement in verifying its own work and iterating carefully until it succeeds

Cons

  • Input/output pricing is exactly 2.5x Sonnet 5's ($5/$25 vs $2/$10)
  • Prompt-cache reads are also 2.5x more expensive ($0.50 vs $0.20/MTok)
  • Still trails Mythos 5 on cybersecurity tasks
  • Latency classification is 'Moderate' — feels slower than Sonnet 5's 'Fast' class
  • In the Claude Code CLI, if the model isn't specified for subagent delegation, it can inherit the (expensive) main session's model
  • Fast mode is only available as a research preview, with premium pricing

Best For

Specification-clear, multi-file complex code (migrations, architectural refactors)Long-running agentic tasks — multi-step work that needs to verify itselfHard verification/judge tasks (adversarial code review, security audits)The strongest general-purpose single-model choice on Claude Max/ProWork that needs a final decision and synthesis before risky/irreversible steps

Claude Sonnet 5

Pros

  • Performance close to Opus 4.8 but at a much lower price ($2/$10 vs $5/$25)
  • The $2/$10 price is now the permanent standard — the planned $3/$15 increase was officially cancelled
  • Latency classification is 'Fast' — feels quicker than Opus 5's 'Moderate' class
  • A lower rate of unwanted behavior compared to Sonnet 4.6
  • The default model for Free and Pro plans at launch, also available on Max/Team/Enterprise
  • 1M-token context window and 128K output limit — the same upper bounds as Opus 5
  • Prompt-cache cost sits at about 40% of Opus 5's — a significant reduction in total cost for high-volume/repetitive work

Cons

  • Trails Opus 5 on the toughest benchmarks like Frontier-Bench/CursorBench
  • Noticeably weaker than current Opus models on cybersecurity tasks
  • Doesn't support fast mode (2.5x speed boost) — that feature is Opus 5/4.8 only
  • Knowledge cutoff of January 2026 — 4 months older than Opus 5
  • Not as durable as Opus 5 on multi-step, long agentic tasks that require self-verification

Best For

Discovery, file scanning, code inventory workTranslation/i18n batch jobs, mechanical edits, routine refactorsPR review, writing tests, everyday code generation — work with a 'clear finish line'High-volume/repetitive subagent delegation (a quality-per-cost advantage)A general-purpose everyday assistant for Free/Pro plan users

Code Comparison

Claude Opus 5
// TypeScript — a specification-clear, hard verification task with Opus 5
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });

async function runMigrationReview(diff: string) {
  const response = await client.messages.create({
    model: "claude-opus-5",
    max_tokens: 4096,
    // Thinking is already on in Opus 5; you steer its depth via
    // `output_config.effort` — "high" is the default, written explicitly here.
    output_config: { effort: "high" },
    messages: [
      {
        role: "user",
        content: `Review this Prisma migration diff adversarially:
try to disprove it on data-loss risk, irreversible
steps, and missing rollback scenarios.\n\n${diff}`,
      },
    ],
  });

  return response.content;
}

// In the Claude Code CLI, write the model explicitly when delegating:
// Agent({ prompt: "...", model: "claude-opus-5" })
Claude Sonnet 5
// TypeScript — high-volume discovery/mechanical work with Sonnet 5
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });

async function translateBatch(entries: string[]) {
  // For "clear finish-line" work like translation/i18n and file scanning,
  // Sonnet 5 delivers quality close to Opus 4.8 at 2.5x lower cost.
  const results = await Promise.all(
    entries.map((text) =>
      client.messages.create({
        model: "claude-sonnet-5",
        max_tokens: 1024,
        // Low effort = fewer tokens, faster response.
        output_config: { effort: "low" },
        messages: [
          {
            role: "user",
            content: `Translate this i18n key from TR to EN, preserve the tone:\n${text}`,
          },
        ],
      })
    )
  );

  return results.map((r) => r.content);
}

// In the Claude Code CLI, a subagent with no model specified inherits
// the main session's model — write the model explicitly for discovery work:
// Agent({ prompt: "scan the src/ directory", model: "claude-sonnet-5" })

Conclusion

There's no clean single-model winner, but there is a clear rule: give specification-clear complex code, migrations, and hard verification work to Opus 5; leave discovery, file scanning, translation, and high-volume mechanical work to Sonnet 5. Don't reverse the order, either — Anthropic's official recommendation is to adjust effort before switching models. Try Sonnet 5 at high effort first; upgrade to Opus 5 only if the result isn't reliable or the task needs multi-turn self-verification.

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FAQ

Frequently Asked Questions

Use Opus 5 for specification-clear, complex, long-running agentic tasks (multi-file refactors, migrations, hard verification); use Sonnet 5 for discovery, file scanning, translation, mechanical edits, and high-volume routine work. Anthropic's official positioning backs this split: Opus 5 stands out for long-agent durability, while Sonnet 5 offers a speed and cost advantage. Rather than a hard rule, try Sonnet 5 at high effort first; move to Opus 5 if it falls short.

Introduction

Whether you should use Claude Opus 5 or Sonnet 5 isn't an abstract "which is better" debate — it's a measurable pricing decision. According to Anthropic's official pricing table, Opus 5 costs $5 per input token and $25 per output token; Sonnet 5 costs $2 and $10. The difference is exactly 2.5x in both directions, and it's permanent: the planned $3/$15 increase for Sonnet 5 was officially cancelled, and $2/$10 became the standard price. The two models come from the same family — both support a 1M token context window, a 128K token output limit (300K on the Batch API), and 5-level effort settings. The difference isn't in the capability ceiling but in positioning: Opus 5 is, in Anthropic's own words, "a step change at the Opus tier" — a clear jump in verifying its own work and iterating until it succeeds on long-horizon agentic tasks. Sonnet 5, meanwhile, is positioned as "near Opus 4.8 performance, at a much lower price." Below, we treat the two models as a practical delegation question: which task should go to which?

Comparison Matrix

Comparison Matrix: Claude Opus 5 / Claude Sonnet 5
FeatureClaude Opus 5Claude Sonnet 5
Input price (MTok)$5$2 (Winner)
Output price (MTok)$25$10 (Winner)
Cache read (MTok)$0.50$0.20 (Winner)
Cache write 5m (MTok)$6.25$2.50 (Winner)
Cache write 1h (MTok)$10$4 (Winner)
Context window1M token1M token
Max output128K (Batch: 300K)128K (Batch: 300K)
Knowledge cutoffMay 2026 (Winner)January 2026
Latency classModerateFast (Winner)
Default efforthighhigh
Fast mode (research preview)Yes (Winner)No
Frontier-Bench positionSOTA, over 2x Opus 4.8 (Winner)Near Opus 4.8
Cybersecurity capabilityBehind Mythos 5 (Winner)Markedly behind Opus models
Launch dateJul 24, 2026Jun 30, 2026
Retirement (earliest)Jul 24, 2027 (Winner)Jun 30, 2027

Deep Dive

Claude Opus 5

Overview

Claude Opus 5 is the model Anthropic announced on July 24, 2026 and officially describes as "a step change at the Opus tier." On Frontier-Bench v0.1, it more than doubles Opus 4.8's performance while lowering the per-task cost; on CursorBench, at the highest effort level, it comes within just 0.5% of Fable 5's peak score, but at half the cost. Anthropic positions the model as "a step change in supporting long-running agents": markedly improved over previous generations at verifying its own work and iterating carefully until it succeeds. It's the new default on the Claude Max plan and the strongest option on Claude Pro. Its one weak point is officially flagged: it's still behind Mythos 5 on cybersecurity tasks. On the API side it comes with a 1M token context, a 128K output limit, and $5/$25 pricing; with a May 2026 knowledge cutoff, it's the most current model in the family.

Ecosystem

Package manager
npm (@anthropic-ai/sdk) / pip (anthropic)
Development environment
Claude Code (CLI)Claude DesktopVS Code + Claude extension
Popular libraries
@anthropic-ai/sdkLangChain (Anthropic integration)LlamaIndex (Anthropic integration)

Claude Sonnet 5

Overview

Claude Sonnet 5 is the model Anthropic announced on June 30, 2026 and positions its performance as "near Opus 4.8, but at a much lower price." At launch it was offered as the default model for Free and Pro plans, and is also available to Max/Team/Enterprise users. On safety, it shows a lower unwanted-behavior rate than Sonnet 4.6, but it's markedly weaker on cybersecurity tasks compared to the current Opus models — a limitation explicitly stated in the official announcement. The most critical development on the price side is that the $2/$10 (input/output MTok) price became the permanent standard price: the planned $3/$15 increase was cancelled. On API features it shares the same upper limits as Opus 5 — 1M token context, 128K output (300K on the Batch API), 5-level effort (default: high), and adaptive thinking. It's in the "Fast" latency classification; its knowledge cutoff is January 2026.

Ecosystem

Package manager
npm (@anthropic-ai/sdk) / pip (anthropic)
Development environment
Claude Code (CLI)Claude DesktopVS Code + Claude extension
Popular libraries
@anthropic-ai/sdkLangChain (Anthropic integration)LlamaIndex (Anthropic integration)

Technical Analysis

Pricing: the 2.5x gap is constant across every axis

In Anthropic's official pricing table (platform.claude.com/docs/en/about-claude/pricing), the difference between Opus 5 and Sonnet 5 isn't only in base input/output — the same ratio holds in prompt-cache pricing too: cache-read at $0.50 vs $0.20/MTok, 5-minute cache-write at $6.25 vs $2.50/MTok, 1-hour cache-write at $10 vs $4/MTok. So from whichever angle you look, Opus 5 is exactly 2.5x more expensive. Simplifying this gap to "Sonnet 5 = the cheap version of Opus 5" would be misleading. That's not Anthropic's official positioning: Sonnet 5 delivers near-Opus-4.8 quality at a much lower price, while Opus 5 differentiates on a separate axis — long-horizon agentic durability and self-verification capacity. Skipping your cache strategy (especially in subagent flows with repeated system prompts) when calculating total cost gives a wrong read on the real cost gap — in a cache-heavy workload the ratio can diverge from the base price. One more tokenizer note: Claude 4.7 and later models produce roughly 30% more tokens for the same text — which can skew a raw $/MTok comparison somewhat from the real per-task cost.

Durability on long-running agentic tasks

Anthropic specifically emphasized this when introducing Opus 5: the model has markedly improved over previous generations at "verifying its own work and iterating carefully until it succeeds." That means not single-turn Q&A, but an agentic task that can sustain the edit-file, run-test, read-error, fix loop for a long stretch. The jump on Frontier-Bench v0.1 and CursorBench (more than 2x Opus 4.8's performance, within 0.5% of Fable 5's peak) backs this claim numerically. Sonnet 5's announcement has a similar improvement too — but the reference point is Sonnet 4.6, not Opus 5: it includes a customer quote saying it "completes complex tasks where previous Sonnet models stalled." So Sonnet 5 is advancing within its own generation, but there's no direct durability comparison against Opus 5 on record. In practice this means: if you need to complete a migration or a multi-file refactor in a single long session with minimal human intervention, Opus 5's self-verification capacity reduces the risk. The same task with Sonnet 5 will likely need more frequent checkpoints — a human-time cost that doesn't show up in the pricing table.

Effort flexibility and the feel of latency

Both models share the same adaptive-thinking architecture: 5 effort levels (low→max), with "high" as the default on both. Anthropic's official guide gives a clear recommendation here: start with the default (high), then adjust up or down based on your evals — meaning effort should be your first lever before switching models. This can be read as an official warning against the reflex of "automatically give every hard task to Opus": sometimes running Sonnet 5 at "high" effort gives a better result than running Opus 5 at "low" effort. The latency difference is clearer: the official model comparison table classifies Sonnet 5 as "Fast" and Opus 5 as "Moderate." This is felt in interactive scenarios where the user is waiting for a response. Opus 5 also offers a research-preview feature called "fast mode" — up to a 2.5x increase in output speed — but it comes with premium pricing, and Sonnet 5 doesn't have this option. Bottom line: if the work is interactive and the effort setting gives sufficient quality, Sonnet 5's speed advantage is one more reason to prefer it. If the work runs in bulk/in the background (batch, subagent, cron), latency stops mattering and the decision comes down entirely to the quality/price balance.

Fit for subagent delegation

One clarification matters here: Anthropic's official documentation doesn't provide a delegation matrix of "give this task type to this model." The official advice stays at the level of "adjust effort first, switch models if needed." The rule "give discovery/mechanical work to Sonnet, specification-clear complex code to Opus" isn't an official Anthropic recommendation — in practice it's a working discipline that teams using coding agents have developed. That said, the two models' official feature differences do support this split: Opus 5's self-verification and long-agent durability make it well suited to "complex work with an unclear finish line," while Sonnet 5's speed + low-cost combination makes it well suited to "high-volume work with a clear finish line." There's a practical trap in the Claude Code CLI: according to the release notes, a subagent's model resolves first from the call's own model value, then from the default subagent setting if that's absent, then from the main session's model if that's absent too. So even a simple file-scanning task where you forgot to specify the model can end up running at the expensive model's price. Explicitly specifying the model on every delegation — "discovery → Sonnet 5", "specification-clear code → Opus 5" — is the safest approach.

Total cost on the same task: why the simple ratio math misleads

In its simplest form, using the 2.5x ratio to say "Opus 5 is 2.5x more expensive than Sonnet 5" is mathematically correct but incomplete in practice. Anthropic's announcement pages show cost-performance charts visually, but they aren't published as a numeric table — so there's no precise official figure for "total cost on the same task." Three factors affect the real total cost: (1) cache usage ratio — in a flow with a repeated system prompt, cache-read/write ratios behave differently from the base price; (2) number of iterations — if Opus 5's self-verification capacity can finish a task in fewer turns, it can end up cheaper in total even at 2.5x the per-token price; (3) tokenizer difference — Claude 4.7 and later models produce roughly 30% more tokens for the same text. Practical advice: run a critical workflow on both models with a small sample (same prompt, same effort level) and measure the actual token count and turn count — decide based on a figure measured on your own workload rather than trusting the theoretical 2.5x ratio.

Retirement/support schedule

Per the official model deprecation page, both models are "Active": Opus 5 will be retired "not before July 24, 2027," Sonnet 5 "not before June 30, 2027." The one-month gap between them doesn't create a practical planning difference, but it's a date every team pinning a model to production should know. The launch dates are close too: Sonnet 5 was announced on June 30, 2026; Opus 5 on July 24, 2026. That 3.5-week gap might make Sonnet 5 look "newer," but the knowledge cutoff dates say the opposite: Opus 5 is May 2026, Sonnet 5 is January 2026 — Opus 5's training data is 4 months more current. One common misconception needs correcting here: undated IDs like claude-opus-5 and claude-sonnet-5 are not "evergreen pointers that resolve to the latest release." In the official documentation's own words, starting with the 4.6 generation and later, an undated ID is that release's canonical model ID and corresponds to a single, fixed snapshot; Anthropic doesn't update the weights of an existing ID, a new release ships under a new ID. The alias behavior only exists for pre-4.6 models. Don't confuse this with short names like default/opus in the Claude Code CLI — those are a separate layer (see Common Pitfalls).

Which One, When

You're writing a multi-file Prisma migration and rollback plan

Recommendation: Opus 5, high effort

It involves irreversible steps; Opus 5's self-verification/durability advantage and its official 'step change on long-agent tasks' positioning come into play here.

You're keeping i18n translation keys current across 8 languages (batch)

Recommendation: Sonnet 5, low-to-medium effort

A clear-finish-line, high-volume, repetitive job — Sonnet 5's price/speed advantage delivers maximum benefit here.

You're doing an adversarial review of a PR, hunting for a security vulnerability

Recommendation: Opus 5, high/xhigh effort

A hard verification/judge task; the official announcement emphasizes that Opus 5 is the strongest option for this kind of work (outside cybersecurity).

You're exploring a new codebase, building a file inventory

Recommendation: Sonnet 5, low effort

Discovery/mechanical work — the speed advantage (latency: Fast) and low cost are worth more here than Opus 5's extra quality.

You need to respond to the user instantly in a real-time chat interface

Recommendation: Sonnet 5 (Opus 5 fast mode if needed)

The latency classification marks Sonnet 5 as 'Fast'; Opus 5's 'Moderate' class can create noticeable delay in interactive use.

You're doing a cybersecurity/exploit analysis task

Recommendation: Neither Opus 5 nor Sonnet 5 — consider the Mythos family

The official announcement explicitly states that both models are weaker in this area compared to the current Opus/Mythos models.

You're setting up a workflow that distributes bulk tasks to subagents

Recommendation: An explicit mix based on task type (Opus 5 + Sonnet 5)

In the Claude Code CLI, a subagent call without a specified model falls back to the main session's model — explicitly specifying the model on every subagent call protects both cost and consistency.

Common Pitfalls

  • Trusting short model names like default / opus in the Claude Code CLI

    Both

    Solution

    These short names can resolve to a different model depending on account/plan and can override your deliberate choice. Always use the full model ID, both in the CLI and in production code (claude-opus-5, claude-sonnet-5).

  • Looking only at base input/output when comparing prices

    Both

    Solution

    Cache-read and cache-write (5m/1h) prices also vary at different ratios; a cost estimate made without accounting for these in workloads with a repeated system prompt is misleading.

  • Not specifying the model when delegating to a subagent in the Claude Code CLI

    Both

    Solution

    A subagent call without a specified model falls back to the default subagent setting, or to the main session's model if that's absent too. Even a simple file-scanning task can end up mistakenly running at Opus 5's price — write the model explicitly on every call.

  • The simplification "Sonnet 5 = the cheap version of Opus 5"

    Both

    Solution

    That's not Anthropic's official positioning — Opus 5 differentiates on the axis of long-agent durability and self-verification, not just 'stronger/more expensive.' Missing this distinction leads to the wrong model choice.

  • Mistaking the 2.5x price ratio for the real total cost difference

    Both

    Solution

    The tokenizer difference (~30% more tokens, Claude 4.7+), the number of iterations, and the cache usage ratio can change the real cost. On a critical workload, run a small real measurement instead of trusting the theoretical ratio.

Migration Guide

Migrating from Sonnet 5 to Opus 5 (or vice versa)

Estimated time: A few hours for a small workflow (testing + measurement); reviewing every delegation point in a large subagent/agent architecture takes 1-2 days
  1. 1Before changing your existing prompt/workflow, try the same task once on Sonnet 5 at 'max' effort — this is always a cheaper first step before switching models
  2. 2If the result is still insufficient, set the model ID to claude-opus-5 — starting with the 4.6 generation, this undated ID is already a fixed snapshot, so you don't need to add a date
  3. 3Review your cache strategy: since cache-read/write cost also increases 2.5x when moving to Opus 5, shorten repeated system prompts where possible or adjust the cache TTL (5m/1h) to your workload
  4. 4In Claude Code CLI subagent/delegation chains, check the model of every call one by one — a call without a specified model falls back to the main session's model
  5. 5Update your latency expectations: Opus 5 is in the 'Moderate' class, Sonnet 5 in the 'Fast' class — test the user experience in interactive flows
  6. 6Update your cost monitoring/budget alerts — the 2.5x price difference changes the total bill markedly, even at the same token usage volume
  7. 7Keep a rollback plan: since both models share the same API shape, changing the model ID requires no code change, so it's quickly reversible

Future Outlook

Claude Opus 5

Per official deprecation policy, Opus 5 will stay Active until at least July 24, 2027 (with a 60-day advance-notice requirement). On Anthropic's roadmap, Opus 5 is positioned as 'a step change at the Opus tier' — no official date has been announced yet for the next generation (Opus 6 or similar). The fast mode feature is still in research preview; no official date has been given for its move to GA.

Claude Sonnet 5

Sonnet 5 will stay Active until at least June 30, 2027. Making the $2/$10 price permanent can be read as a signal of Anthropic's intent to keep the Sonnet tier positioned as the long-term 'default/accessible model.' No official date has been announced for the next Sonnet generation.

Golden Insight

The most valuable takeaway isn't in the two models themselves, but hidden in Anthropic's official advice: adjust the effort level before switching models. Raising effort from low to max within the same model is a cheaper and more predictable lever than switching models for most tasks. The right mental model isn't a one-dimensional model choice but a two-dimensional decision: adjust effort first; if the result is still insufficient and the task genuinely needs long-horizon self-verification, switch to Opus 5. In agentic workflows, this distinction directly saves money: instead of writing a fixed rule like "hard task = Opus," keep effort variable and measure the real failure rate.

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