Claude Sonnet 5
Claude Sonnet 5 is worth evaluating for coding, rag, and agents when its provider route and context window match the workload.
Use it for
- Teams evaluating coding, rag, and agents
- Workloads that can use a 1m context window
- Buyers comparing 4 tracked provider routes
Do not use it for
- Workloads where another current model has stronger sourced task evidence
- Family
- Claude 5
- Released
- 2026-06-30
- Context
- 1m
- Max output
- 128,000
- Architecture
- Decoder Only
- Knowledge cutoff
- 2026-01
- Specialization
- general
- Openness
- Proprietary
- License
- ProprietaryCommercial use: conditional
- Weights
- Not released
- Code
- Unknown
- Training
- Fine-tuned
Cheapest of 5 routes · Anthropic · cache read $0.200
About
Claude Sonnet 5 is Anthropic's next-generation Sonnet model for agentic coding, tool use, computer use, and professional work. It is a proprietary decoder-only model with a 1M-token context window, 128K max output, multimodal vision, adaptive thinking, function calling, structured outputs, prompt caching, and Batch API support. It is available through the Claude API, AWS Bedrock, Google Cloud Vertex AI, Microsoft Foundry preview, and OpenRouter. Anthropic lists durable standard pricing at $3/1M input and $15/1M output tokens, with introductory $2/$10 pricing through 2026-08-31.
Claude Sonnet 5 is a proprietary model in the Claude 5 family. The structured metadata tracks a 1m-token context window, multimodal input, reasoning, function calling, tool use, structured outputs, and code execution. This page tracks provider routes through Anthropic, AWS Bedrock, GCP Vertex AI, and 2 more, with the cheapest tracked route listed at $2 input and $10 output per 1M tokens. Headline tracked benchmarks include SWE-bench Verified 85.2, SWE-bench Pro 63.2, and SWE-bench Multilingual 78.3.
Top use-case fit: coding, agents, and build tasks
Coding
Q/$ D2 relevant benchmarks in the decision map.
RAG
Included by capability and metadata signals in the decision map.
Agents
Q/$ D1 relevant benchmark in the decision map.
Provider price ladder
Compare all 5Compare API pricing across 4 providers for input and output tokens, batch, and cached reads when available.
| Provider | Input / 1M | Output / 1M | Batch in / out | Cache | Route |
|---|---|---|---|---|---|
| Anthropic | $2.00 | $10.00 | $1.00 / $5.00 | read $0.200 / 5m $2.50 / 1h $4.00 | Serverless |
| GCP Vertex AI | $2.00 | $10.00 | $1.00 / $5.00 | read $0.200 / 5m $2.50 / 1h $4.00 | Serverless |
| OpenRouter | $2.00 | $10.00 | - | read $0.200 / 5m $2.50 / 1h $4.00 | Serverless |
| AWS Bedrock | - | - | - | - | ServerlessPartial |
Available via routers & gateways(16)
LiteLLM
GatewayOpen-source Python SDK and proxy server that unifies 100+ LLM APIs behind a single OpenAI-compatible interface, with load balancing, cost tracking, and configurable failover.
OpenRouter
HybridUnified hybrid gateway to 400+ models from 60+ providers via a single OpenAI-compatible API, with optional auto-routing that selects the best model per prompt.
Portkey
GatewayProduction AI gateway routing to 1,600+ LLMs with failover, load balancing, semantic caching, and guardrails; Apache 2.0 core is fully self-hostable with the complete feature set.
AIRouter
RouterCommercial LLM router that analyzes incoming requests and routes to the optimal model for cost/quality/latency via a drop-in OpenAI-compatible API, with a privacy-preserving embedding mode that avoids sending prompt content.
Amazon Bedrock Intelligent Prompt Routing
RouterAWS Bedrock's native intelligent prompt router that routes prompts between Anthropic Claude model tiers (Haiku/Sonnet) based on predicted task complexity, with no extra per-routing charge.
Azure AI Foundry Model Router
RouterMicrosoft Azure AI Foundry's native model router that uses a trained ML model to route each prompt in real time to the optimal Azure-hosted model, with Balanced/Cost/Quality mode selection and automatic failover.
Capabilities
Benchmark peer barsfor Coding
Benchmark scores(16)
| Benchmark | Score | Version | Evaluation | Source |
|---|---|---|---|---|
| SWE-bench Verified | 85.2 | SWE-bench Verified; Anthropic standard configuration, adaptive thinking at max effort, default sampling, average over 5 trialsObserved 2026-06-30 | — | Source |
| SWE-bench Pro | 63.2 | SWE-bench Pro; Anthropic standard configuration, adaptive thinking at max effort, default sampling, average over 5 trialsObserved 2026-06-30 | — | Source |
| SWE-bench Multilingual | 78.3 | SWE-bench Multilingual; Anthropic standard configuration, adaptive thinking at max effort, default sampling, average over 5 trialsObserved 2026-06-30 | — | Source |
| Terminal-Bench 2.1 | 80.4 | Terminal-Bench 2.1; mini-SWE-agent harness on GKE, 1x timeout rate, 3x memory ceiling, xhigh effort, 445 trialsObserved 2026-06-30 | — | Source |
| Humanity's Last Exam — With Tools | 57.4 | Humanity's Last Exam with web search, web fetch, programmatic tool calling, and code execution; Claude Opus 4.6 grader; 1M total-token capObserved 2026-06-30 | — | Source |
| BrowseComp — Multi-Agent | 86.6 | BrowseComp multi-agent; web search, web fetch, programmatic tool calling, code execution; 10M-token limit with context compactionObserved 2026-06-30 | — | Source |
| BrowseComp | 84.7 | BrowseComp single-agent; adaptive thinking at maximum effort, 10M-token limit with context compaction triggered at 200kObserved 2026-06-30 | — | Source |
| OSWorld-Verified | 81.2 | OSWorld-Verified; 361 tasks, 1080p Ubuntu VM, 100 action steps, adaptive thinking at max effort, pass@1 averaged over 5 runsObserved 2026-06-30 | — | Source |
| GDP.pdf | 81.6 | GDP.pdf with Python tools and image cropping tool; internal harness, Opus 4.7 judge, mean criteria pass rate averaged over 5 runsObserved 2026-06-30 | — | Source |
| Humanity's Last Exam | 43.2 | Humanity's Last Exam; no tools; reasoning-only; thinking auto; 1M total-token cap; Claude Opus 4.6 graderObserved 2026-06-30 | — | Source |
| CursorBench | 61.2 | CursorBench 3.1Observed 2026-06-30 | Configuration: Sonnet 5 Max Harness: CursorBench 3.1 Evaluator: Cursor Confidence: confirmed Notes: Highest CursorBench 3.1 score across Cursor's published effort configurations for this base model. | Source |
| CursorBench | 61.5 | CursorBench 3.2Observed 2026-07-18 | Configuration: Sonnet 5 Max Harness: CursorBench 3.2 productized Cursor-agent workflow Evaluator: Cursor Confidence: confirmed Cost/task: $6.45 Tokens/task: 92,882 Steps/task: 86 Notes: Cursor vendor-reported result; not independently reproducible. Results are subject to variance, and small score differences may not be statistically meaningful. | Source |
| CursorBench | 58.7 | CursorBench 3.2Observed 2026-07-18 | Configuration: Sonnet 5 Extra High Harness: CursorBench 3.2 productized Cursor-agent workflow Evaluator: Cursor Confidence: confirmed Cost/task: $4.16 Tokens/task: 52,871 Steps/task: 67 Notes: Cursor vendor-reported result; not independently reproducible. Results are subject to variance, and small score differences may not be statistically meaningful. | Source |
| CursorBench | 56.9 | CursorBench 3.2Observed 2026-07-18 | Configuration: Sonnet 5 High Harness: CursorBench 3.2 productized Cursor-agent workflow Evaluator: Cursor Confidence: confirmed Cost/task: $3.19 Tokens/task: 39,483 Steps/task: 57 Notes: Cursor vendor-reported result; not independently reproducible. Results are subject to variance, and small score differences may not be statistically meaningful. | Source |
| CursorBench | 52.4 | CursorBench 3.2Observed 2026-07-18 | Configuration: Sonnet 5 Medium Harness: CursorBench 3.2 productized Cursor-agent workflow Evaluator: Cursor Confidence: confirmed Cost/task: $2.16 Tokens/task: 26,200 Steps/task: 46 Notes: Cursor vendor-reported result; not independently reproducible. Results are subject to variance, and small score differences may not be statistically meaningful. | Source |
| CursorBench | 47.7 | CursorBench 3.2Observed 2026-07-18 | Configuration: Sonnet 5 Low Harness: CursorBench 3.2 productized Cursor-agent workflow Evaluator: Cursor Confidence: confirmed Cost/task: $1.30 Tokens/task: 16,269 Steps/task: 33 Notes: Cursor vendor-reported result; not independently reproducible. Results are subject to variance, and small score differences may not be statistically meaningful. | Source |
Migration checks
No linked migration route is available for this model yet.
Rankings & picks(4)
Comparison and alternatives
Browse all comparisons →Frequently asked questions
What is the context window of Claude Sonnet 5?
Claude Sonnet 5 has a context window of 1m tokens.
What is the max output of Claude Sonnet 5?
Claude Sonnet 5 can generate up to 128,000 output tokens.
How much does Claude Sonnet 5 cost?
Claude Sonnet 5 pricing ranges from $2.00/1M to $2/1M input tokens depending on the provider.
When was Claude Sonnet 5 released?
Claude Sonnet 5 was released on 2026-06-30.
Which providers offer Claude Sonnet 5?
Claude Sonnet 5 is available from 5 providers: Anthropic, AWS Bedrock, GCP Vertex AI, OpenRouter, Microsoft Foundry.
What benchmarks has Claude Sonnet 5 been tested on?
Claude Sonnet 5 has been evaluated on 16 benchmarks, including SWE-bench Verified, SWE-bench Pro, SWE-bench Multilingual, Terminal-Bench 2.1, Humanity's Last Exam — With Tools.
Cheapest of 5 routes · Anthropic · cache read $0.200