Model comparison
Claude Fable 5 vs Deepseek Coder v2
Claude Fable 5 is the stronger model overall, scoring 66.8 to 35.9 on the Noometry Index.
Last verified . 17 shared benchmarks.
DeepSeekSummary
- They share 17 benchmarks with published results for both. Claude Fable 5 scores higher in 8 categories and Deepseek Coder v2 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Fable 5 leads 88.5 to 34.9.
- Deepseek Coder v2 has downloadable open weights; the other is API-only.
Side by side
| Claude Fable 5 | Deepseek Coder v2 | |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 66.8 | 35.9 |
| Released | 2026-06-07 | 2024-06-17 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 128K | — |
| Input $ / M tokens | $10 | — |
| Output $ / M tokens | $50 | — |
| Results tracked | 62 | 24 |
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Category by category
Coding Claude Fable 5 leads
Claude Fable 5: 70.6 (#4), Deepseek Coder v2: 38.1 (#183)
| Benchmark | Claude Fable 5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Coding | 1519 | 1251 |
| DeepSWE | 69.9% | — |
| FrontierCode | 53.5% | — |
| LMArena WebDev | 1625 | — |
| FrontierSWE | 47% | — |
| SciCode | 61% | — |
| GSO | 78.4% | — |
| WeirdML | 91.9% | — |
| BigCodeBench Instruct | — | 48.2% |
| MirrorCode | 63.9% | — |
| BigCodeBench Complete | — | 59.7% |
| ALE-Bench | 2,041 | — |
| HumanEval+ | — | 82.3% |
| MBPP+ | — | 75.1% |
Agentic & Tool Use Not comparable
Claude Fable 5: 54.0 (#2), Deepseek Coder v2: —
| Benchmark | Claude Fable 5 | Deepseek Coder v2 |
|---|---|---|
| APEX-Agents | 63.6% | — |
| Remote Labor Index | 16.1% | — |
| τ²-bench Banking | 39.7% | — |
| PostTrainBench | 41.8% | — |
| GBAEval | 74.5% | — |
| GDP.pdf | 30% | — |
| LMArena Search | 1230 | — |
| Vending-Bench 2 | 5,680 | — |
Reasoning Claude Fable 5 leads
Claude Fable 5: 76.8 (#6), Deepseek Coder v2: 23.6 (#176)
| Benchmark | Claude Fable 5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Hard Prompts | 1508 | 1207 |
| ARC-AGI-2 | 89.2% | — |
| SimpleBench | 81.9% | — |
| Kagi LLM Benchmark | 91.4% | — |
| NYT Connections (extended) | 92.7% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 28.6% | — |
| Chess Puzzles | 41% | — |
| EnigmaEval | 39.3% | — |
| EBR-Bench | 39.5% | — |
| Mystery Game Puzzles | 52% | — |
| DTBench | 98.4% | — |
| LMCA | 61.1% | — |
| Surface Evolver Bench | 95% | — |
| Bench to the Future 3 | 0.13 | — |
| Epoch Capabilities Index | 162.06 | — |
| WinoGrande | — | 83.7% |
Math Claude Fable 5 leads
Claude Fable 5: 88.5 (#5), Deepseek Coder v2: 34.9 (#190)
| Benchmark | Claude Fable 5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Math | 1519 | 1241 |
| FrontierMath (Tiers 1-3) | 87% | — |
| FrontierMath Tier 4 | 90.2% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 95% | — |
| FrontierMath Erdős | 0% | — |
| GSM8K | — | 94.5% |
Knowledge Claude Fable 5 leads
Claude Fable 5: 62.2 (#25), Deepseek Coder v2: 32.3 (#212)
| Benchmark | Claude Fable 5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Expert | 1534 | 1181 |
| GPQA Diamond | 85.9% | — |
| SimpleQA Verified | 70.7% | — |
| ARC (AI2) Challenge | — | 64.3% |
Multimodal Not comparable
Claude Fable 5: 45.3 (#17), Deepseek Coder v2: —
| Benchmark | Claude Fable 5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Vision | 1324 | — |
| Blueprint-Bench 2 | 38.6% | — |
| Furniture Assembly | 35.8% | — |
| LMArena Document | 1496 | — |
Multilingual Claude Fable 5 leads
Claude Fable 5: 57.3 (#9), Deepseek Coder v2: 36.3 (#240)
| Benchmark | Claude Fable 5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Non-English | 1481 | 1182 |
| LMArena Chinese | 1543 | 1201 |
| LMArena French | 1505 | 1185 |
| LMArena German | 1486 | 1164 |
| LMArena Japanese | 1506 | 1126 |
| LMArena Korean | 1488 | 1104 |
| LMArena Russian | 1504 | 1188 |
| LMArena Spanish | 1498 | 1153 |
Instruction Following Claude Fable 5 leads
Claude Fable 5: 78.6 (#8), Deepseek Coder v2: 61.7 (#242)
| Benchmark | Claude Fable 5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Instruction Following | 1502 | 1180 |
Long Context Claude Fable 5 leads
Claude Fable 5: 46.3 (#23), Deepseek Coder v2: 37.0 (#224)
| Benchmark | Claude Fable 5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Longer Query | 1509 | 1219 |
Writing & Preference Claude Fable 5 leads
Claude Fable 5: 75.9 (#5), Deepseek Coder v2: 38.2 (#253)
| Benchmark | Claude Fable 5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Text | 1491 | 1191 |
| LMArena Creative Writing | 1494 | 1120 |
| LMArena Multi-Turn | 1504 | 1177 |
| EQ-Bench Creative Writing | 1943 | — |
| EQ-Bench 4 | 1340 | — |
Frequently asked questions
Is Claude Fable 5 better than Deepseek Coder v2?
Claude Fable 5 is the stronger model overall, scoring 66.8 to 35.9 on the Noometry Index.
Is Claude Fable 5 or Deepseek Coder v2 better for coding?
Claude Fable 5 scores higher on coding benchmarks: 70.6 versus 38.1 in the Noometry coding category.
How many benchmarks do Claude Fable 5 and Deepseek Coder v2 share?
17 benchmarks have published results for both models. Claude Fable 5 has 62 scored results on Noometry and Deepseek Coder v2 has 24.