Estimate from the version's published specs, benchmarks and reviews, 0-5; scores are only comparable within one criteria year. Scored as launched (Claude Sonnet 4.5, 29 Sep 2025): 200K-token standard window (Anthropic's model page: 200K; a 1M-token configuration existed as a beta, used by Cognition and noted on the launch post, so scored at the standard 200K); price $3 in / $15 out per 1M tokens = $6 blended at 3:1; text and image input. Anthropic: SWE-bench Verified 77.2%, OSWorld 61.4%; its Terminal-Bench figure (Terminus 2 harness) is not Terminal-Bench 4.0, so coding is null. Reasoning null: AA's current page re-scores 4.5 Sonnet on index v4.1 and no launch-version score was opened. Speed null (no tokens/s). Reviews: Willison (preview access), Zvi, CodeRabbit (code-review benchmark), Cognition (vendor, real agent rebuild), Every (writing tests).[1]
My initial impressions were that it felt like a better model for code than GPT-5-Codex, which has been my preferred coding model since it launched a few weeks ago
My tentative evaluation is a qualified yes. This is likely a big leap in some ways. If I had to pick one 'best coding model in the world' right now it would be Sonnet 4.5.
Sonnet 4.5 gets you close to Opus-level performance at a fraction of the price, making it a pragmatic sweet spot for teams reviewing code at scale.
With Sonnet 4.5, we're seeing the biggest leap since Sonnet 3.6 (the model that was used with Devin's GA): planning performance is up 18%, end-to-end eval scores up 12%, and multi-hour sessions are dramatically faster and more reliable.
Then Anthropic dropped Sonnet 4.5, and within 48 hours my workflow collapsed from two chat interfaces into one.
| Claude Sonnet 4.5 is probably the "best coding model in the world" (at least for now) · 2025. 9. 29. | 0.80 |
|---|---|
| Rebuilding Devin for Claude Sonnet 4.5: Lessons and Challenges · 2025. 9. 29. | 0.80 |
| Claude Sonnet 4.5 Is A Very Good Model · 2025. 10. 1. | 0.80 |
| Claude Sonnet 4.5: Better performance but a paradox · 2025. 10. 3. | 0.70 |
| We Tested Claude Sonnet 4.5 for Writing and Editing · 2025. 10. 23. | 0.80 |
독자들의 사진으로, 출처가 있는 핀의 미디어와 별도로 표시됩니다. 먹거나 본 것을 평가하고, 레스토랑 핀에서는 사진에 바로 요리를 태그해 보세요.
첫 번째 항목은 항상 핀의 출처입니다. 전체 신뢰도는 각 자료가 위의 시작·종료 시각을 얼마나 확실히 뒷받침하는지에 대한 가중 평균이며, 자료는 최신 자료보다 180일 오래될 때마다 가중치가 절반이 됩니다.
게시물은 “Sep 29, 2025”로 날짜가 표시돼 있으며 “Claude[2] Sonnet 4.5는 오늘부터 어디서나 이용 가능하다”고 밝혔다. 문서 페이지에는 “Released September 29, 2025”라고 나와 있고, TechCrunch[4]도 “월요일”에 출시됐다고 보도했다.
Anthropic's[1][3] model page: claude-sonnet-4-5-20250929, 200K context window, 64K max output, $3/$15 per million tokens, extended thinking, text and images in, a January 2025 reliable knowledge cutoff, "Released September 29, 2025".
Anthropic's[1] system card for Claude[2] Sonnet 4.5, "a new hybrid reasoning large language model" (September 2025), with the alignment and safety evaluations behind its ASL-3 release.
TechCrunch, 2025-09-29: "On Monday, Anthropic[1][3] launched a new frontier model called Claude[2] Sonnet 4.5" at Sonnet 4's $3/$15; researcher David Hershey saw it code autonomously for up to 30 hours; it arrives less than two months after Claude Opus 4.1.
CNBC, 2025-09-29: available to all users from the $183 billion startup; Mike Krieger says it will be the default and recommends it for "basically every use case"; it runs autonomously for 30 hours against Opus 4's seven.
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원본 제목: Claude Sonnet 4.5 Released
| 벤치마크 | Claude Sonnet 4.5 | Claude Opus 4.1 | Claude Sonnet 4 | GPT-5 | Gemini 2.5 Pro |
|---|---|---|---|---|---|
| 에이전트 코딩 (SWE-bench Verified) | 77.2% / 82.0% with parallel test-time compute | 74.5% / 79.4% with parallel test-time compute | 72.7% / 80.2% with parallel test-time compute | 72.8% (GPT-5) / 74.5% (GPT-5-Codex) | 67.2% |
| 에이전트 터미널 코딩 (Terminal-Bench) | 50.0% | 46.5% | 36.4% | 43.8% | 25.3% |
| 에이전트 도구 사용 (τ2-bench), 소매 | 86.2% | 86.8% | 83.8% | 81.1% | — |
| 에이전트 도구 사용 (τ2-bench), 항공 | 70.0% | 63.0% | 63.0% | 62.6% | — |
| 에이전트 도구 사용 (τ2-bench), 통신 | 98.0% | 71.5% | 49.6% | 96.7% | — |
| 컴퓨터 사용 (OSWorld) | 61.4% | 44.4% | 42.2% | — | — |
| 고등학교 수학 경시대회 (AIME 2025) | 100% (python) / 87.0% (no tools) | 78.0% | 70.5% | 99.6% (python) / 94.6% (no tools) | 88.0% |
| 대학원 수준 추론 (GPQA Diamond) | 83.4% | 81.0% | 76.1% | 85.7% | 86.4% |
| 다국어 질의응답 (MMMLU) | 89.1% | 89.5% | 86.5% | 89.4% | — |
| 시각적 추론 (MMMU validation) | 77.8% | 77.1% | 74.4% | 84.2% | 82.0% |
| 금융 분석 (Finance Agent) | 55.3% | 50.9% | 44.5% | 46.9% | 29.4% |