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SWE-bench Verified leaderboard

Claude Opus 4.5 leads
79.2%
models measured
38
lead over #2
+3.4 pts
median
63.8%

Leader on SWE-bench Verified · read October 22

swe_bench_verified.py


        # SWE-bench Verified, read October 22
        leaders = {
            "Claude Opus 4.5": 79.2%,    "Gemini 3 Flash Preview": 75.8%,    "MiniMax M2.5": 75.8%,
        }
      

On October 22, 2026, 42 of our catalog's models had a SWE-bench Verified result, and Anthropic Claude Opus 4.5 led with 79.2%, ahead of Google Gemini 3 Flash Preview at 75.8%.

SWE-bench hands a model a real GitHub issue from an open source Python project and asks for a patch. The number is the share of issues where the patch makes the project tests pass. The board also publishes what one attempt cost, which is how we compute cost per solved task.

Role in the index

A coding board we show beside the Vibe Coding Index, not inside it: the index keeps the six boards it was defined on, so a score does not move every time a board is added. Read the methodology

SWE-bench Verified results for models in the catalog
# Model Result Cost per attempt Evidence Coding index Output $/Mtok
1 Claude Opus 4.5Anthropic 79.2% Not published 44.0 $25.00
2 Gemini 3 Flash PreviewGoogle 75.8% $0.356 43.7 $3.00
3 MiniMax M2.5MiniMax 75.8% $0.0733 37.2 $1.20
4 Claude Opus 4.6Anthropic 75.6% $0.5515 57.2 $25.00
5 Claude Sonnet 4.5Anthropic 74.8% Not published 39.5 $15.00
6 GPT-5OpenAI 74.4% Not published 38.8 $10.00
7 GPT-5.2OpenAI 72.8% $0.4736 55.9 $14.00
8 GPT-5.2-CodexOpenAI 72.8% $0.4494 45.4 $14.00
9 GLM 5Z.ai 72.8% $0.5344 41.7 $3.20
10 Kimi K2 0711Moonshot AI 71.2% Not published Not benchmarked $2.30
11 Kimi K2.5Moonshot AI 70.8% $0.1466 38.6 $2.85
12 DeepSeek V3.2DeepSeek 70.0% $0.4478 30.0 $0.88
13 Qwen3 Coder 480B A35BQwen 69.6% Not published Not benchmarked $1.50
14 GLM 4.6Z.ai 68.2% Not published 8.8 $2.20
15 Claude Haiku 4.5Anthropic 66.6% $0.3309 35.6 $5.00
16 Claude 3.7 SonnetRetiredAnthropic 66.4% Not published Not benchmarked $15.00
17 GPT-5.1OpenAI 66.0% $0.3062 40.4 $10.00
18 GPT-5.1-CodexOpenAI 66.0% $0.5889 15.3 $10.00
19 o4 MiniOpenAI 64.6% Not published Not benchmarked $4.40
20 GLM 4.5Z.ai 64.2% Not published Not benchmarked $2.20
21 Claude 3.5 SonnetRetiredAnthropic 63.4% Not published Not benchmarked $15.00
22 Kimi K2 ThinkingMoonshot AI 63.4% $0.4383 Not benchmarked $2.50
23 MiniMax M2MiniMax 61.0% $0.4283 Not benchmarked $1.02
24 Qwen3 Coder 30B A3B InstructQwen 60.4% Not published Not benchmarked $0.44
25 GPT-5 MiniOpenAI 59.8% $0.0355 34.2 $2.00
26 o3OpenAI 58.4% $0.3337 Not benchmarked $8.00
27 Devstral 2 2512Mistral AI 53.8% Not published Not benchmarked $2.00
28 Gemini 2.5 ProGoogle 53.6% $0.2884 19.1 $10.00
29 Qwen2.5 Coder 32B InstructQwen 47.0% Not published Not benchmarked $1.00
30 o3 MiniOpenAI 42.4% Not published Not benchmarked $4.40
31 DeepSeek V3 0324DeepSeek 42.0% Not published Not benchmarked $1.07
32 Claude 3.5 HaikuRetiredAnthropic 40.6% Not published Not benchmarked $4.00
33 GPT-4.1OpenAI 39.6% $0.1463 Not benchmarked $8.00
34 GPT-4oOpenAI 38.8% Not published Not benchmarked $10.00
35 GPT-5 NanoOpenAI 34.8% $0.0381 Not benchmarked $0.40
36 Gemini 2.5 FlashGoogle 28.7% $0.1339 Not benchmarked $2.50
37 gpt-oss-120bOpenAI 26.0% $0.0571 Not benchmarked $0.50
38 GPT-4.1 MiniOpenAI 23.9% $0.4352 Not benchmarked $1.60
39 GPT-4OpenAI 22.4% Not published Not benchmarked $60.00
40 Llama 4 MaverickMeta Llama 21.0% $0.3137 Not benchmarked $1.00
41 Claude 3 OpusRetiredAnthropic 15.8% Not published Not benchmarked $75.00
42 Llama 4 ScoutMeta Llama 9.1% $0.1156 Not benchmarked $0.50

Only models in our catalog are listed, and each appears once with its best published run. 42 rows were read from the source on October 22, 2026, and rows that match no catalog model are left out. Cost per attempt is what swebench.com reports one task cost on the run behind the result, in US dollars. Only some runs report it.