Claude Sonnet 5: Benchmarks, Pricing & How It Compares

On June 30, 2026, Anthropic shipped Claude Sonnet 5, the newest model in its mid-tier "Sonnet" line and, by the company's own framing, its most agentic Sonnet to date. The pitch is simple to state and harder to verify: Sonnet 5 plans multi-step work, drives browsers and terminals, and runs autonomously at a level Anthropic says recently required larger, more expensive models — while costing the same on paper as Sonnet 4.6 and well under half of Opus 4.8 at its introductory rate.

That positioning — near-flagship quality at workhorse prices — is exactly the kind of claim worth pulling apart before you rewire your stack. This guide walks through what actually changed versus Sonnet 4.6, the benchmarks Anthropic published, real pricing including a tokenizer change that quietly affects your bill, where you can run the model today, and honest head-to-head verdicts: Sonnet 5 against Sonnet 4.6, against Claude Opus 4.8, and against the GPT and Gemini competition. Every number below comes from Anthropic's launch post, its system card, and the official model docs — nothing from guesswork.

What is Claude Sonnet 5?

Claude Sonnet 5 is a general-purpose frontier model positioned in the middle of Anthropic's lineup — above the cheaper Haiku 4.5 and below the flagship Opus 4.8, with the premium-priced Fable 5 sitting at the top of the range. Its calling card is agentic work: not just answering a prompt, but planning a sequence of steps, calling tools, reading the result, and continuing without a human nudging it at every turn. Anthropic describes it plainly as a model built to plan, use browsers and terminals, and run autonomously.

The headline specs:

• Context window: 1M tokens. (Launch-day reports noted the window briefly appeared smaller before settling at the full 1M.)
• Max output: 128k tokens, raisable to 300k via the batch-API beta header output-300k-2026-03-24.
• Adaptive thinking: always on, with effort defaulting to high on the API and in Claude Code.
• Knowledge / training cutoff: January 2026.
• Latency: Fast.
• Model ID: claude-sonnet-5 on the Claude API.

"Adaptive thinking always on" is the most consequential of these for day-to-day use. Rather than you toggling a reasoning mode, the model scales its internal deliberation to the task — light for a quick rewrite, heavier for a multi-file refactor or a research question. Combined with the high effort default, the practical result is that Sonnet 5 spends more compute reasoning before it acts than Sonnet 4.6 did out of the box, which likely contributes to the more reliable task-completion early users report (more on that below).

What's actually new versus Sonnet 4.6?

If you're already running Sonnet 4.6 in production, this is the section that matters. The gains are real and they're not uniform — reasoning, tool use, and long-context coding moved the most. At a glance, the version-over-version deltas on the headline benchmarks:

• Terminal-Bench 2.1: +13.4 points (67.0% → 80.4%) — the biggest single jump
• Humanity's Last Exam, no tools: +8.6 points (34.6% → 43.2%)
• Humanity's Last Exam, with tools: +10.6 points (46.8% → 57.4%)
• SWE-bench Pro: +5.1 points (58.1% → 63.2%)
• OSWorld-Verified: +2.7 points (78.5% → 81.2%)
• GDPval-AA v2 knowledge work: +223 (1395 → 1618)

Reasoning

On Humanity's Last Exam, a deliberately brutal academic benchmark, Sonnet 5 scores 43.2% with no tools versus Sonnet 4.6's 34.6% — an 8.6-point jump. With tools enabled, Sonnet 5 reaches 57.4% versus 46.8%. That with-tools number is the eye-catcher: it nearly matches Opus 4.8's 57.9%, meaning that on this particular test, once you give Sonnet 5 a calculator and a search tool, the reasoning gap to the flagship almost closes.

Tool use and the terminal

Terminal-Bench 2.1 measures how well a model operates inside a shell — running commands, reading output, recovering from errors. Sonnet 5 jumps to 80.4% from Sonnet 4.6's 67.0%, a 13.4-point gain and the single largest improvement in the headline table. For anyone running agents that live in a terminal, this is the most tangible upgrade.

Agentic coding

On SWE-bench Pro — note, the harder Pro variant, not Verified — Sonnet 5 scores 63.2% versus 58.1%. Cursor's own internal CursorBench tells a similar story: 57% versus 49% for Sonnet 4.6, which Cursor publicly called a meaningful step up. The long-context coding picture is even stronger: on ProgramBench, Sonnet 5 lands in the 76–86% band versus Sonnet 4.6's 52–74%, closing most of the distance to Opus 4.8's 80–90%. If your work involves reasoning across a large codebase rather than a single file, that's the number to watch.

Knowledge work

GDPval-AA v2 scores professional knowledge work — the kind of analysis, drafting, and synthesis a consultant or analyst does. Here Sonnet 5 posts 1618, up substantially from Sonnet 4.6's 1395. It's also the one headline metric where Sonnet 5 edges out Opus 4.8 (1615), which we'll come back to.

The behavioral change: it finishes

Benchmarks aside, the most-cited difference from early users isn't a number — it's completion. The recurring sentiment on Reddit's r/AI_Agents was that Sonnet 5 "is almost as good as Opus 4.8, but very fast and cheaper," and that it actually drives long agentic chains to done rather than stalling, asking for permission, or declaring victory early. That tracks with the higher Terminal-Bench score, the always-on adaptive thinking, and the high effort default. For background on how agentic coding models are evaluated and deployed, our AI coding agents guide covers the broader landscape.

How does Sonnet 5 do on benchmarks?

Here are the headline benchmarks from Anthropic's launch post. Opus 4.8 is included as a reference ceiling; Sonnet 4.6 as the model you're likely upgrading from.

Two things to read carefully here. First, the coding benchmark is SWE-bench Pro, the harder variant — don't mistake it for the more commonly quoted SWE-bench Verified, where scores run higher. Second, the pattern is consistent: Sonnet 5 sits clearly above 4.6 across the board, and clearly below Opus 4.8 on everything except the reasoning-with-tools and knowledge-work rows, where it nearly matches or nudges ahead.

Anthropic's system card adds a few more evals worth knowing. On BrowseComp 25, an agentic web-search benchmark, Sonnet 5 scores 84.7% — run with a 10M-token operating limit and context compaction kicking in at 200k, which gives you a sense of how Anthropic expects long-horizon agentic sessions to behave. The same card is where the cross-vendor numbers live, which we'll get to in the competition section.

Independent benchmarks: how Sonnet 5 lands on Artificial Analysis

Everything above comes from Anthropic. For an independent read, Artificial Analysis scores Claude Sonnet 5 (Max) at 38.16 on its Intelligence Index v4.3.2 (October 2026). Two things to note before you compare that to any number you remember: AA rebased the index from v4.1.1 to v4.3.2, so every score on the board moved because the benchmark basket changed, not because the models did — there is no conversion factor, and older Sonnet 5 figures in the low 50s are v4.1.1-era. And AA publishes a separate score per effort setting, so the tier matters: Sonnet 5 runs 24.26 bare, 31.66 at high, 34.38 at xhigh and 38.16 at max.

At each model's top tier on v4.3.2, Sonnet 5 (Max, 38.16) is effectively level with GPT-5.5 (Xhigh, 38.36) — a 0.2-point gap is noise, not a ranking — and still behind both Opus tiers: Claude Opus 4.7 (Max) 40.69 and Claude Opus 4.8 (Max) 41.79. Against the model you are most likely upgrading from, Claude Sonnet 4.6 (Max) scores 30.06, so Sonnet 5 is a genuine ~8-point gain. The shape of the result is the same as it was at launch: the “near-flagship” framing holds for agentic work more than for heavy reasoning.

Where Sonnet 5 genuinely closes the gap is agentic knowledge work. On Artificial Analysis's AA-Briefcase and GDPval-AA benchmarks — which test producing accurate, well-presented professional outputs through a tool-using agent loop — Sonnet 5 sits just ahead of Opus 4.8, trailing only Fable 5 (which isn't generally available). That independently corroborates Anthropic's core pitch: near-Opus agentic knowledge-work quality at a Sonnet sticker price.

On heavy reasoning it's a different story. On CritPt, a frontier physics-reasoning benchmark from researchers at Argonne and UIUC, Sonnet 5 scores 17% — 14 points above Sonnet 4.6, but behind GLM-5.2, Opus 4.8, Fable 5, and GPT-5.5. If your workload is heavy-reasoning-first rather than agentic knowledge work, Opus 4.8 is still the stronger pick.

The cost catch the sticker price hides. Sonnet 5 lists at $2/$10 per million, well under Opus 4.8's $5/$25 — but Artificial Analysis found it "works harder": it burned ~40% more output tokens per Intelligence Index task than Sonnet 4.6 and used ~3× the agentic turns on the knowledge-work evals (this scales with the effort setting — max used roughly 6× the turns of low on GDPval-AA). On AA's Intelligence Index v4.3.2 run that shows up in the bill: Sonnet 5 at max effort cost $5.09 per index task against Opus 4.8 (Max) at $4.08 — about 25% more, despite Opus's 2.5x higher per-token price. Dropping Sonnet 5 to high effort cuts it to $1.79 per task for 31.66 index points, which is the trade most teams actually want. So budget on measured token usage at your effort setting, not on the headline per-token gap.

What does Sonnet 5 cost — and what's the tokenizer catch?

List pricing is straightforward. The wrinkle is underneath it.

Sonnet 5 runs at $2 input / $10 output per million tokens, and that is now the permanent rate. Anthropic announced $2/$10 as introductory pricing through August 31, 2026, with a step up to $3/$15 scheduled for September 1 — then cancelled it. The pricing page states it plainly: the $2/$10 rate “is now the standard price” and “the previously scheduled increase to $3/$15 per million input/output tokens on September 1, 2026 will not occur.” So Sonnet 5 is a third cheaper per token than Sonnet 4.6’s $3/$15, not merely equal to it.

Except it's not quite that clean. Sonnet 5 ships with an updated tokenizer that maps the same text to roughly 1.0–1.35x more tokens (Anthropic's pricing page puts the average increase at about 30% for Claude 4.7 and later). So a third off the rate card does not mean a third off the bill: the same prompt and the same response now count as more tokens. Reddit flagged the tokenizer change as a quiet price increase when the step-up to $3/$15 was still scheduled; with that increase cancelled, the net effect for most workloads is a real saving against Sonnet 4.6, just smaller than the rate card suggests.

Practical takeaway: don't assume flat spend just because the per-token list price matches. Run a representative sample of your real prompts through both models and compare the actual token counts and dollar totals, not the rate card. If your workload is token-heavy — large contexts, long outputs — the tokenizer change is where the savings can quietly erode.

Where can you use Claude Sonnet 5?

Availability on day one was unusually broad — Anthropic clearly coordinated launch partners. Sonnet 5 is the new default model for Free and Pro users on claude.ai, and available to Max, Team, and Enterprise. First-party surfaces:

• Claude Code
• Claude API — model ID claude-sonnet-5
• claude.ai and Cowork/Chat
• AWS Bedrock — anthropic.claude-sonnet-5
• Google Vertex AI and Microsoft Foundry

Third-party coding tools went live the same day: VS Code (via the official extension), GitHub Copilot, Cursor, OpenRouter (with the matching $2/$10 promo), and Command Code. The tooling partners pushed support live on day one rather than waiting weeks — a sign of how coordinated the launch was. The model IDs you'll actually paste into configs:

claude-sonnet-5            # Claude API
anthropic.claude-sonnet-5  # AWS Bedrock
output-300k-2026-03-24     # batch-API beta header to raise max output to 300k

If you route Claude through OpenRouter for billing or fallback flexibility, our walkthrough on using Claude Code with OpenRouter covers the setup. For editor workflows, the trade-offs between Cursor's agent and a raw Sonnet session are unpacked in Cursor Composer vs Claude Sonnet.

Sonnet 5 vs Opus 4.8: when should you use which?

This is the real decision for most teams, because the two models now overlap heavily while Opus costs noticeably more — $5/$25 versus Sonnet's $2/$10 (2.5x on both input and output). The short version: Sonnet 5 is the new default workhorse; Opus 4.8 is still the accuracy ceiling.

Where Opus 4.8 still wins. Look back at the benchmark table. Opus leads SWE-bench Pro by about 6 points (69.2 vs 63.2), and also leads Terminal-Bench 2.1, OSWorld-Verified, and Humanity's Last Exam with no tools. On ProgramBench long-context coding, Opus's 80–90% band edges Sonnet 5's 76–86%. If your task is raw, hard accuracy on agentic coding or computer use — the kind of work where a 6-point gap means a real difference in success rate on a tough repository — Opus is still the safer call. Anthropic also recommends Opus for cyber work that needs reduced guardrails, since Sonnet 5 has weaker cyber capability and ships with cyber safeguards on by default.

Where Sonnet 5 wins. Price ($2/$10 vs Opus's $5/$25), speed (Fast latency), and — notably — GDPval-AA v2 knowledge work, the one headline metric where Sonnet 5 (1618) actually edges Opus 4.8 (1615). On that benchmark for professional knowledge tasks — analysis, drafting, synthesis — Sonnet 5 essentially matches the flagship for less. For the very large volume of agentic coding and tool-use work that doesn't sit right at the difficulty frontier, Sonnet 5 is "near-Opus" enough that the price and speed delta usually wins.

Safety is a quiet Sonnet 5 strength. On the system card's robustness evals, Sonnet 5 tied Opus 4.8 for best-in-class prompt-injection resistance and actually beat it on honesty:

A 0.19% prompt-injection attack success rate — matching Opus and far below Sonnet 4.6's 1.41%, GPT-5.5's 3.08%, and Gemini 3.5 Flash's 6.66% — matters a lot if you're deploying agents that read untrusted web content or process third-party documents. The MASK lying rate of 3.1% (versus Sonnet 4.6's 13.3% and even Opus's 6.1%) is the kind of honesty improvement that's easy to ignore until an agent confidently fabricates something in production.

One organizational nuance worth flagging if you're on an Enterprise plan: Premium seats still default to Opus 4.8. So depending on your seat tier, the "which model" answer may already be made for you — check before assuming everyone's on the new default.

How does Sonnet 5 compare to GPT-5.6 and Gemini 3.5 Pro?

Here's where we have to be honest about what does and doesn't exist. Anthropic published no official comparison between Sonnet 5 and GPT-5.6 or Gemini 3.5 Pro. That's not an oversight to paper over with vibes — GPT-5.6 had not launched as of June 30, 2026 (track that release in our GPT-5.6 release watch), and the cross-vendor numbers in Anthropic's system card are against GPT-5.5 and Gemini 3.5 Flash, not the Pro tier. Treat any Sonnet-5-vs-GPT-5.6 or Sonnet-5-vs-Gemini-3.5-Pro table you see elsewhere as unofficial extrapolation.

What we can show is the apples-to-apples slice from the system card — Sonnet 5 against the GPT and Gemini models Anthropic actually tested:

Even within that limited comparison, the leadership is benchmark-dependent. Sonnet 5 leads on SWE-bench Pro (63.2 vs GPT-5.5's 58.6 and Gemini 3.5 Flash's 55.1), but GPT-5.5 edges Sonnet 5 on Terminal-Bench 2.1 (83.4 vs 80.4). So "best agentic coder" isn't a clean win — it depends which axis you weight. Anyone claiming Sonnet 5 categorically beats the field on agentic coding is overstating it.

For a real GPT-5.6 or Gemini 3.5 Pro comparison, you'll need each vendor's own published figures, and you should flag them as non-apples-to-apples since they won't be run under Anthropic's harness. Our Gemini 3.5 guide tracks Google's side; we'll update the GPT-5.6 comparison once OpenAI ships and publishes numbers under comparable conditions.

Should you switch to Claude Sonnet 5?

For most teams already on Sonnet 4.6, the answer is yes — with eyes open on cost. The reasoning, tool-use, and long-context coding gains are large and consistent, the safety profile is materially better, and at $2/$10 it is cheaper per token than the Sonnet 4.6 you are leaving. The behavioral improvement — agents that finish rather than stall — is the kind of thing that's hard to capture in a benchmark but shows up immediately in real usage.

Three caveats keep this honest:

1. Mind the tokenizer. The rate card says a third cheaper than Sonnet 4.6, but the new tokenizer counts up to 1.35x more tokens for the same text, and AA measured ~40% more output tokens per task at max effort. Measure your real workload before banking the saving.
2. Opus 4.8 still wins raw accuracy. Sonnet 5 beats Opus only on GDPval knowledge work. On SWE-bench Pro, Terminal-Bench, OSWorld, and HLE-no-tools, Opus leads — sometimes by enough to matter on hard tasks. Keep Opus in the toolbox for the frontier-difficulty jobs and cyber work.
3. It's not a clean crown. Early sentiment was a genuine upgrade, not a coronation. Several community threads noted the gap to Opus 4.8 was smaller than expected but didn't fully close, and Opus loyalists weren't entirely won over. The realistic read: Sonnet 5 is the best value in the Claude lineup, not the outright best model.

A sensible default policy: route the bulk of your agentic coding, tool use, and knowledge work to Sonnet 5; reserve Opus 4.8 for the hardest accuracy-critical jobs and anything needing reduced cyber guardrails; keep Haiku 4.5 for high-volume, latency-sensitive, simple calls. If you're choosing models across the whole ecosystem rather than just within Anthropic's lineup, the AI coding agents guide sets the broader context.

If you're a founder or eng lead trying to operationalize a multi-model setup — routing, evals, agent harnesses, the boring plumbing that makes any of this reliable in production — Codersera places vetted remote engineers who've already built it. That's the only pitch here; the rest is just the numbers.

FAQ

What is Claude Sonnet 5's model ID and context window?

The Claude API model ID is claude-sonnet-5; on AWS Bedrock it's anthropic.claude-sonnet-5. The context window is 1M tokens, with 128k max output (raisable to 300k via the batch-API beta header output-300k-2026-03-24).

How much does Claude Sonnet 5 cost?

$2 per million input tokens and $10 per million output tokens. That started as introductory pricing through August 31, 2026, but Anthropic's pricing page now states it is the standard price and that the planned September 1 increase to $3/$15 will not occur. Note the updated tokenizer counts roughly 1.0–1.35x more tokens for the same text, so your real saving against Sonnet 4.6's $3/$15 is smaller than the rate card implies.

Is Claude Sonnet 5 better than Opus 4.8?

Not across the board. Sonnet 5 beats Opus 4.8 only on GDPval-AA v2 knowledge work (1618 vs 1615), nearly matches it on Humanity's Last Exam with tools (57.4% vs 57.9%), and ties it on prompt-injection safety. Opus 4.8 still leads on SWE-bench Pro (69.2% vs 63.2%), Terminal-Bench 2.1, OSWorld-Verified, and HLE with no tools, and is recommended for cyber work. Sonnet 5 wins on price and speed.

How does Sonnet 5 compare to GPT-5.6 and Gemini 3.5 Pro?

There is no official Anthropic comparison to either — GPT-5.6 had not launched as of June 30, 2026, and the system card's cross-vendor figures are against GPT-5.5 and Gemini 3.5 Flash. In that limited set, Sonnet 5 leads SWE-bench Pro (63.2% vs GPT-5.5's 58.6% and Gemini 3.5 Flash's 55.1%), but GPT-5.5 edges it on Terminal-Bench 2.1 (83.4% vs 80.4%). Any GPT-5.6 or Gemini 3.5 Pro head-to-head is unofficial.

What does Claude Sonnet 5 score on the Artificial Analysis Intelligence Index?

38.16 at max effort on Intelligence Index v4.3.2 (October 2026), with 34.38 at xhigh, 31.66 at high and 24.26 bare. AA rebased the index from v4.1.1 to v4.3.2, so scores in the low 50s you may have seen for Sonnet 5 are v4.1.1-era figures and do not convert — the basket of benchmarks changed, not the model.

Is Claude Sonnet 5 deprecated?

It is listed under “Legacy models (still available)” in Anthropic's model docs as of October 2026, alongside Claude Opus 5, Opus 4.8 and Sonnet 4.6. It still works and still costs $2/$10, but the current mid-tier is Claude Sonnet 5.5 at the same price, and Anthropic's advice for new projects is to start with Claude Opus 5.5.

Where can I use Claude Sonnet 5?

It's the default for Free and Pro users on claude.ai and available to Max, Team, and Enterprise. It's live in Claude Code, the Claude API, AWS Bedrock, Google Vertex, and Microsoft Foundry, plus third-party tools from day one: VS Code, GitHub Copilot, Cursor, and OpenRouter (with a matching $2/$10 promo).

Should I upgrade from Sonnet 4.6 to Sonnet 5?

For most teams, yes — the reasoning, tool-use, and long-context coding gains are large and consistent, safety is meaningfully better, and at $2/$10 Sonnet 5 is cheaper per token than Sonnet 4.6. The caveat is the tokenizer: measure your real token counts before banking the saving. If you are starting fresh in October 2026, go to Claude Sonnet 5.5 instead — same price, and 56.00 against Sonnet 5's 38.16 on Artificial Analysis's Intelligence Index v4.3.2 at max effort.