by Anthropic
Anthropic's mid-tier flagship: the best combination of speed and intelligence, built for high-volume agentic coding and computer use at 40% below Opus 4.8 pricing.
Sonnet 5 fits engineering teams running high-volume agentic coding and computer-use work who want near-Opus quality at Sonnet pricing. It's the wrong pick for voice or video-first products, since it has no native audio or video I/O, and for configs still pinned to non-default sampling parameters. Max output runs to 128,000 tokens on the synchronous API.
| Job | Input | Output | Total |
|---|---|---|---|
| Summarise a 20-page PDF | $0.090 | $0.015 | $0.105 |
| Support reply | $0.0060 | $0.0045 | $0.010 |
| One coding agent run | $0.600 | $0.300 | $0.900 |
Budgets: 20-page PDF = 30k in / 1k out · Support reply = 2k in / 300 out · Coding agent run = 200k in / 20k out. Computed from the vendor's per-token prices at render time; cached-input discounts are not applied.
$3 per 1M input tokens and $15 per 1M output tokens at standard pricing, identical to Sonnet 4.6's rate card. An introductory discount of $2/$10 per 1M tokens runs through August 31, 2026, offsetting the new tokenizer's higher per-request token counts. Prompt cache reads bill at 0.1x the standard input rate, and the Batch API is 50% cheaper but excluded from Zero Data Retention, with batch data held up to 29 days.
Claude Sonnet 5, Anthropic's mid-tier flagship model released in 2026, sits between Haiku 4.5 and Opus 4.8 in Anthropic's current lineup. It leads on GPQA Diamond at 96.2% and posts 84.7% on ARC-AGI-2, running adaptive hybrid reasoning by default for agentic coding and computer-use automation.
Reads
Writes
82.1% SWE-bench Verified
First model to clear the 80% mark on SWE-bench Verified, the benchmark most agentic coding teams weigh first.
1M-Token Context Window
128,000 max output tokens on the synchronous Messages API, extending to 300,000 on the Batch API.
Computer Use
Scores 81.2% on OSWorld-Verified and 80.4% on Terminal-Bench 2.1, both sharp jumps from Sonnet 4.6's 78.5% and 67.0%.
Adaptive Thinking
Runs by default on every request unless explicitly disabled, replacing Sonnet 4.6's opt-in extended-thinking mode.
Prompt Caching
Cache reads are billed well below the standard input rate, cutting costs on repeat-context agentic workloads.
SWE-bench Verified, first model to break the 80% ceiling
Source: Claude Sonnet 5 launch coverage, June 30, 2026Pricier than 80% of the 104 GA models with a published price, in the top third on SWE-bench Verified (rank 9 of 39), and one of 41 that document a zero-data-retention option.
| Measure | This model | Rank | Median |
|---|---|---|---|
| Blended price (3:1)$ per 1M tokens | $6.00/M | #81 / 104 | peer median $1.73/M |
| SWE-bench Verified% solved | 82.1% | #9 / 39 | peer median 76.5% |
| GPQA Diamond% correct | 96.2% | #1 / 63 | peer median 87.8% |
Ranks are against GA models on Hokai that publish the same figure; ties share a rank.
A benchmark is an exam, not the job. Scores transfer unevenly between tasks, so weigh the one closest to your workload and read every figure with its source.
| Model | Lab | Context | In / out per 1M | Reads and writes |
|---|---|---|---|---|
| Anthropic | 1M | $3 / $15 | text, image, pdf → text | |
| Anthropic | 1M | $5 / $25 | text, image, pdf → text | |
| Anthropic | 1M | $3 / $15 | text, image, pdf → text | |
| 1M | $2 / $12 | text, image, audio, video, pdf → text |
Training data
Trained on a curated mix of public web text, licensed datasets, and synthetic reasoning traces with a reliable knowledge cutoff of January 2026. Uses the same tokenizer introduced with Claude Opus 4.7, producing roughly 30% more tokens per input than Sonnet 4.6's tokenizer.
| Name | Endpoint | Auth |
|---|---|---|
| Anthropic Claude API | https://platform.claude.com/docs/en/api/rate-limits | API Key |
| AWS Bedrock | https://aws.amazon.com/blogs/machine-learning/introducing-claude-sonnet-5-on-aws-anthropics-most-capable-sonnet-model/ | AWS IAM |
| Microsoft Foundry (Azure) | https://platform.claude.com/docs/en/build-with-claude/claude-in-microsoft-foundry | Azure AD |
| Google Vertex AI | https://platform.claude.com/docs/en/build-with-claude/claude-on-vertex-ai | GCP IAM |
Explicitly set thinking mode
Pass thinking: { type: 'disabled' } to turn off adaptive thinking, or leave it default for adaptive reasoning.Adaptive thinking runs by default on every request, unlike Sonnet 4.6, and consumes part of the max_tokens budget.
State an explicit reporting bar for code review
"Report every bug you find, including low-severity ones, even if below your usual bar."
Sonnet 5 follows instructions more literally and may silently drop low-severity findings it judges not worth reporting unless told otherwise.
Adaptive thinking on by default
Requests without an explicit thinking field ran without thinking on Sonnet 4.6 but run with adaptive thinking on Sonnet 5, consuming part of the max_tokens budget for the same request.
Workaround: Pass thinking: { type: 'disabled' } explicitly for requests that need the old no-thinking behavior, and re-check max_tokens limits for workloads migrated from Sonnet 4.6.
Sampling params now error at non-default values
Setting temperature, top_p, or top_k to anything other than the default returns a 400 error, unlike on Sonnet 4.6 where these were accepted.
Workaround: Remove these parameters from request payloads during migration, or explicitly pass the default value.
New tokenizer inflates token counts ~30%
The same input text produces roughly 30% more tokens than under Sonnet 4.6's tokenizer, so usage fields and pre-flight token counts are not directly comparable across generations.
Workaround: Recount tokens against Sonnet 5 directly rather than reusing cached counts from Sonnet 4.6, and rebudget max_tokens accordingly.
Fewer reported low-severity code review findings
The model investigates code as thoroughly as before and finds the same bugs, but converts fewer investigations into reported findings when it judges them below the stated severity bar, which can look like reduced recall even though detection ability improved.
Workaround: Explicitly instruct the model to report every finding regardless of severity when running code review or audit tasks.
claude-sonnet-5 · 30 Jun 2026
Initial release. First model to break 80% SWE-bench Verified (82.1%). Adaptive thinking on by default, new tokenizer, $3/$15 pricing with $2/$10 introductory rate through Aug 31, 2026.
claude-sonnet-4-6 · 24 Mar 2026
Predecessor. 79.6% SWE-bench Verified, 58.1% SWE-bench Pro, 78.5% OSWorld-Verified.
Standard pricing charges $3 for a million input tokens and $15 for a million output tokens, matching Sonnet 4.6's rate card. Through August 31, 2026, Anthropic discounts that to $2/$10 per 1M tokens to cushion the higher counts from the new tokenizer, and cached reads bill at a tenth of the normal input price. Batch requests run 50% cheaper than the synchronous API but give up Zero Data Retention eligibility.
Claude Sonnet 5 has no standalone free tier: it's the default model on claude.ai's Free and Pro consumer plans, subject to standard message-rate limits, but full-rate API access requires a paid API account with no free monthly quota. Teams wanting the model at zero marginal cost only get it through the consumer chat interface, not the developer API.
Inside Anthropic's own lineup, Claude Opus 4.8 suits teams that need the highest coding ceiling and can absorb higher per-token pricing, while Claude Sonnet 4.6 fits teams not yet ready to re-tune token budgets around the new tokenizer. Outside Anthropic, Gemini 3.1 Pro and GPT-5.4 both compete directly on agentic coding and long-context tasks.
Claude Sonnet 5 posts a higher SWE-bench Verified score than GPT-5.4, the first model in either lineup to clear the 80% mark on that benchmark. GPT-5.4 counters with a native Computer Use API built into OpenAI's own stack, while Sonnet 5's computer-use gains come from Anthropic's OSWorld-Verified and Terminal-Bench improvements instead. Teams already standardized on OpenAI's tooling have less reason to switch; teams choosing fresh get a real coding-benchmark edge from Sonnet 5.
Getting started just needs an Anthropic API key and a request to the Messages API with the model field set to claude-sonnet-5. Existing Sonnet 4.6 integrations need any explicit temperature, top_p, or top_k overrides removed, since non-default values now return a 400 error. Claude Code and GitHub Copilot users can switch model versions directly in their settings without touching API code.
Claude Sonnet 5 is Anthropic's fifth-generation Sonnet-tier model, released June 30, 2026. Anthropic positions it as a drop-in upgrade for Sonnet 4.6 that closes most of the coding gap to Opus 4.8 while keeping Sonnet's speed and price. It is a dense, hybrid-reasoning Transformer with adaptive thinking on by default; Anthropic has not disclosed a parameter count.
Sonnet 5 uses the tokenizer introduced with Opus 4.7, so identical text now produces roughly 30% more tokens than under Sonnet 4.6's tokenizer. Anthropic's reliable knowledge cutoff for the model is January 2026.
Deployment spans the direct Claude API, AWS Bedrock, Microsoft Foundry, and Google Vertex AI (listed as coming soon at launch), plus day-one access through Claude Code and GitHub Copilot. Anthropic holds SOC 2 Type I and Type II, ISO 27001:2022, and ISO/IEC 42001:2023 certifications, signs HIPAA Business Associate Agreements, and offers Zero Data Retention outside the Batch API.
Safety partners for the June 30, 2026 system card include METR, Apollo Research, and the UK AI Security Institute. Anthropic reports lower misalignment, hallucination, and sycophancy rates than Sonnet 4.6, plus better prompt-injection resistance; the model does not cross the automated AI R&D capability threshold and shows only limited bio/chem uplift.
Specifications on this page (context window, token prices, benchmark scores, licence) are read from Anthropic's own model card and documentation. The verdict is Hokai's reading of them, not the provider's claim.