Model comparison
DeepSeek Coder 6.7B vs GPT-5 Nano
GPT-5 Nano has enough public results to be ranked (#234); DeepSeek Coder 6.7B does not yet, so treat this comparison as directional.
Last verified . 1 shared benchmarks.
DeepSeekSummary
- They share 1 benchmark with published results for both. DeepSeek Coder 6.7B scores higher in 1 category and GPT-5 Nano in 0 categories; one gap is clear of the uncertainty.
- DeepSeek Coder 6.7B has downloadable open weights; the other is API-only.
Side by side
| DeepSeek Coder 6.7B | GPT-5 Nano | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 37.1 | 33.4 |
| Released | 2023-11-02 | 2025-08-07 |
| Weights | Open | Proprietary |
| Context window | — | 400K |
| Max output | — | 128K |
| Input $ / M tokens | — | $0.05 |
| Output $ / M tokens | — | $0.40 |
| Results tracked | 9 | 48 |
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Category by category
Coding DeepSeek Coder 6.7B leads
DeepSeek Coder 6.7B: 35.2 (#216), GPT-5 Nano: 33.3 (#248)
| Benchmark | DeepSeek Coder 6.7B | GPT-5 Nano |
|---|---|---|
| SWE-bench Verified (bash only) | — | 34.8% |
| WeirdML | — | 38.1% |
| BigCodeBench Instruct | 35.5% | — |
| LMArena Coding | — | 1351 |
| BigCodeBench Complete | 43.8% | — |
| ALE-Bench | — | 718.67 |
| HumanEval+ | 71.3% | — |
| MBPP+ | 65.6% | — |
Agentic & Tool Use Not comparable
DeepSeek Coder 6.7B: —, GPT-5 Nano: 25.6 (#99)
| Benchmark | DeepSeek Coder 6.7B | GPT-5 Nano |
|---|---|---|
| Terminal-Bench | — | 21.8% |
| Berkeley Function Calling Leaderboard | — | 51.5% |
Reasoning Not comparable
DeepSeek Coder 6.7B: —, GPT-5 Nano: 16.4 (#291)
| Benchmark | DeepSeek Coder 6.7B | GPT-5 Nano |
|---|---|---|
| Epoch Capabilities Index | 88.88 | 139.39 |
| ARC-AGI-2 | — | 2.6% |
| Kagi LLM Benchmark | — | 62.2% |
| ARC-AGI-1 | — | 20.7% |
| Chess Puzzles | — | 27% |
| LMArena Hard Prompts | — | 1329 |
| Mystery Game Puzzles | — | 9% |
| DTBench | — | 62.7% |
| LMCA | — | 7.9% |
| ForecastBench | — | 59.1 |
| WinoGrande | 57.6% | — |
Math Not comparable
DeepSeek Coder 6.7B: —, GPT-5 Nano: 29.1 (#221)
| Benchmark | DeepSeek Coder 6.7B | GPT-5 Nano |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 20% |
| FrontierMath Tier 4 | — | 2.4% |
| OTIS Mock AIME 2024-2025 | — | 81.1% |
| ProofBench | — | 12% |
| Omni-MATH | — | 54.6% |
| LMArena Math | — | 1318 |
| MATH Level 5 | — | 95.2% |
| FrontierMath (Feb 2025 set) | — | 8.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
| GSM8K | 21.3% | — |
Knowledge Not comparable
DeepSeek Coder 6.7B: —, GPT-5 Nano: 35.8 (#166)
| Benchmark | DeepSeek Coder 6.7B | GPT-5 Nano |
|---|---|---|
| GPQA Diamond | — | 69.4% |
| SimpleQA Verified | — | 11.7% |
| MMLU-Pro | — | 77.8% |
| Vectara Hallucination Rate | — | 10.5% |
| GPQA (HELM) | — | 67.9% |
| LMArena Expert | — | 1321 |
| ARC (AI2) Challenge | 36.4% | — |
| MMLU | 36.4% | — |
Multimodal Not comparable
DeepSeek Coder 6.7B: —, GPT-5 Nano: 30.7 (#102)
| Benchmark | DeepSeek Coder 6.7B | GPT-5 Nano |
|---|---|---|
| LMArena Vision | — | 1159 |
| VPCT | — | 37.2% |
Multilingual Not comparable
DeepSeek Coder 6.7B: —, GPT-5 Nano: 45.5 (#167)
| Benchmark | DeepSeek Coder 6.7B | GPT-5 Nano |
|---|---|---|
| LMArena Non-English | — | 1313 |
| LMArena Chinese | — | 1355 |
| LMArena German | — | 1329 |
| LMArena Korean | — | 1269 |
| LMArena Russian | — | 1296 |
| LMArena Spanish | — | 1360 |
Instruction Following Not comparable
DeepSeek Coder 6.7B: —, GPT-5 Nano: 75.2 (#72)
| Benchmark | DeepSeek Coder 6.7B | GPT-5 Nano |
|---|---|---|
| IFEval | — | 93.2% |
| LMArena Instruction Following | — | 1306 |
Long Context Not comparable
DeepSeek Coder 6.7B: —, GPT-5 Nano: 31.3 (#275)
| Benchmark | DeepSeek Coder 6.7B | GPT-5 Nano |
|---|---|---|
| Fiction.LiveBench | — | 44.4% |
| LMArena Longer Query | — | 1313 |
Writing & Preference Not comparable
DeepSeek Coder 6.7B: —, GPT-5 Nano: 39.4 (#244)
| Benchmark | DeepSeek Coder 6.7B | GPT-5 Nano |
|---|---|---|
| LMArena Text | — | 1320 |
| LMArena Creative Writing | — | 1250 |
| EQ-Bench Creative Writing | — | 705 |
| WildBench | — | 80.6% |
| LMArena Multi-Turn | — | 1311 |
Frequently asked questions
Is DeepSeek Coder 6.7B better than GPT-5 Nano?
GPT-5 Nano has enough public results to be ranked (#234); DeepSeek Coder 6.7B does not yet, so treat this comparison as directional.
Is DeepSeek Coder 6.7B or GPT-5 Nano better for coding?
DeepSeek Coder 6.7B scores higher on coding benchmarks: 35.2 versus 33.3 in the Noometry coding category.
How many benchmarks do DeepSeek Coder 6.7B and GPT-5 Nano share?
1 benchmark has published results for both models. DeepSeek Coder 6.7B has 9 scored results on Noometry and GPT-5 Nano has 48.