none reviewed yet · 0 benchmark observations · latest capture Sep 8, 2026
Inspect the evidenceClaude Sonnet 5
Teams that need Claude-grade code quality across a whole org at moderate cost
Saved editorial fit for your current task lens; not a benchmark result
How scoring worksVerified rates (Sep 8, 2026) · 100 runs / month at your token settings
Adjust workloadAt a glance
9 facts- Provider
- Anthropic
- Type
- API model
- Access
- Anthropic API, Claude apps (including Free plan), AWS Bedrock, Claude Code
- Context
- 1,000,000 tokens
- Maximum output
- 128K tokens
- License / weights
- Proprietary
- Input modalities
- text, image, file
- Output modalities
- text
- Pricing notes
- $2 in / $10 out per 1M; cache read $0.20, cache write $2.50
The practical trade-offs
Documented strengths
- SWE-bench Verified 85.2% at $2/$10 is the best correctness-per-dollar in the Anthropic line
- 1M multimodal context and 128K output at mid-tier price
- Only Claude in this set available on the consumer Free plan
- Well-sampled Arena row (7,006 votes)
Limitations to check
- TTFT 203.67 s at max effort is among the worst measured here
- Design Arena 1292 and Arena 1543 are mid-pack visually
- Anthropic docs give no separate Sonnet-5 frontend claims
- Several AA effort variants have no published score
Evidence & conditions
- Evidence source 1
docs.aws.amazon.comDate not recorded - Evidence source 2
anthropic.comDate not recorded - Evidence source 3
arena.aiDate not recorded - Evidence source 4
benchlm.aiDate not recorded - Evidence source 5
benchlm.aiDate not recorded - Evidence source 6
artificialanalysis.aiDate not recorded
No comparable benchmark observations are recorded for this entry.
Source reports, measured results, and editorial assessments are separate evidence types. Source dates do not imply a new benchmark run. Capture dates are shown when recorded; otherwise we say the capture date was not recorded. Recorded dates are compared with this catalogue snapshot (Sep 11, 2026), not today’s date.
How this page is assessed
Quality claims follow Method AIS-V2.
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