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Best small open models for coding

Updated November 2026

As of November 2026, the best option is Qwen3.8 27B by Alibaba (Qwen), with a Coding score of 83.5, followed by Ternary Bonsai 2 27B (81.0) and Qwen3.6 27B (80.6).

Ranked by the average of LiveCodeBench (competitive programming) and SWE-bench Verified (fixing real GitHub issues). Where a lab did not report one of them, the index model’s estimate is used and marked.

#ModelLabCoding scoreIndexParamsMemory (4-bit)API / 1MLicense
1Qwen3.8 27BAlibaba (Qwen)83.5≈77.027B~17.9 GB$0.13Apache-2.0
2Ternary Bonsai 2 27BPrismML81.0≈74.627.4B~18.2 GBself-hostApache-2.0
3Qwen3.6 27BAlibaba (Qwen)80.674.027B~17.9 GB$0.90Apache-2.0
4Muse Glimmer 30BMeta79.5≈72.629.6B~19.2 GB$0.53Apache-2.0
5Qwen3.5 27BAlibaba (Qwen)77.870.627B~17.9 GB$0.69Apache-2.0
6Qwen3.6 35B-A3BAlibaba (Qwen)76.972.235B (3B active)~22.6 GB$0.031Apache-2.0
7Kolibri-1Aleph Alpha76.268.378.1B (3.5B active)~49.6 GBself-hostApache-2.0
8Qwen3.5 35B-A3BAlibaba (Qwen)72.369.935B (3B active)~22.6 GB$0.24Apache-2.0
9Spark-X2.6 4BSparkLLM (XHToken)70.2≈67.54.1B~3.4 GBself-hostApache-2.0
10Nanbeige4.2 3BNanbeige (Kanzhun)68.070.44.2B~3.8 GBself-hostApache-2.0
11Granite 4.2 30BIBM (Granite)66.8≈67.030B~21.4 GBself-hostApache-2.0
12Gemma 4 31BGoogle66.070.130.7B~21.9 GB$0.16Apache-2.0
13Nemotron 3.5 LightningNVIDIA62.4≈63.631.6B (3.6B active)~22.4 GB$0.049OpenMDW-1.1
14Granite 4.2 8BIBM (Granite)62.4≈63.58B~6.9 GB$0.082Apache-2.0
15OLMo 3.1 32B ThinkAi2 (OLMo)62.1≈57.032.2B~22 GBself-hostApache-2.0

Memory covers the weights only; long contexts need more. Scores are mostly lab-reported, so gaps of 1–2 points are noise. See the methodology, or filter the full leaderboard yourself.

Head to head

Questions

What is the best small open-weight model for coding?

As of November 2026, the best option is Qwen3.8 27B by Alibaba (Qwen), with a Coding score of 83.5, followed by Ternary Bonsai 2 27B (81.0) and Qwen3.6 27B (80.6).

How is this list ranked?

Ranked by the average of LiveCodeBench (competitive programming) and SWE-bench Verified (fixing real GitHub issues). Where a lab did not report one of them, the index model’s estimate is used and marked.

Which of the top five needs the least memory?

Qwen3.8 27B, at about 17.9 GB with 4-bit quantization.

Which is the cheapest to use through an API?

Qwen3.6 35B-A3B, at $0.031 per million tokens from the cheapest provider on OpenRouter.

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