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SWE-bench Multilingual Leaderboard

coding13 models · Updated October 2026

On the SWE-bench Multilingual benchmark, Gemini 3 Flash ranks #1 with a score of 72.7, while DeepSeek: DeepSeek V3.2 offers the best score-per-dollar at $0.80/1M output tokens. The full ranking, with cost per million tokens, is below.

💰 Best value
DeepSeek: DeepSeek V3.2 — score 59.0 at $0.80/1M output tokens
#ModelScoreOutput / 1MContext
1Gemini 3 FlashOpenCode72.7$3.001M
2Anthropic: Claude Opus 4.6Anthropic72.0$25.001M
3Anthropic: Claude Opus 4.5Anthropic70.7$25.00200K
4Z.ai: GLM 5Z.ai69.7$1.92205K
5Gemini 3 ProGoogle DeepMind68.7——
6MiniMax 2.5Regolo AI68.3$3.50190K
7MoonshotAI: Kimi K2.5MoonshotAI67.3$3.00262K
8Anthropic: Claude Sonnet 4.5Anthropic67.0$15.001M
9OpenAI: GPT-5.2OpenAI66.7$14.00400K
10OpenAI: GPT-5.2-CodexOpenAI66.3$14.00400K
11Anthropic: Claude Haiku 4.5Anthropic64.7$5.00200K
12DeepSeek: DeepSeek V3.2DeepSeek59.0$0.80164K
13OpenAI: GPT-5 MiniOpenAI39.7$2.00400K

What does SWE-bench Multilingual test?

Evaluation framework with 2,294 real GitHub software-engineering problems.

Frequently asked questions

What is the SWE-bench Multilingual benchmark?

Evaluation framework with 2,294 real GitHub software-engineering problems.

Which model is best on SWE-bench Multilingual?

Gemini 3 Flash (OpenCode) currently leads the SWE-bench Multilingual leaderboard with a score of 72.7.

What is the best value model on SWE-bench Multilingual?

DeepSeek: DeepSeek V3.2 offers the best score-per-dollar on SWE-bench Multilingual — a score of 59.0 at $0.80 per 1M output tokens.

Pricing is indicative — confirm with the provider before production use. Updated October 2026.