Model comparison
DeepSeek V4 Pro vs OLMo 2 Furious 13B
DeepSeek V4 Pro is the stronger model overall, scoring 54.2 to 29.2 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Allen Institute for AI (Ai2)Summary
- The widest gap is in math, where DeepSeek V4 Pro leads 64.6 to 21.3.
Side by side
| DeepSeek V4 Pro | OLMo 2 Furious 13B | |
|---|---|---|
| Provider | DeepSeek | Allen Institute for AI (Ai2) |
| Noometry Index | 54.2 | 29.2 |
| Released | 2026-04-24 | 2024-12-31 |
| Weights | Open | Open |
| Context window | 1M | — |
| Max output | 393K | — |
| Input $ / M tokens | $0.43 | — |
| Output $ / M tokens | $0.87 | — |
| Results tracked | 48 | 12 |
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Category by category
Coding DeepSeek V4 Pro leads
DeepSeek V4 Pro: 52.2 (#31), OLMo 2 Furious 13B: 28.1 (#309)
| Benchmark | DeepSeek V4 Pro | OLMo 2 Furious 13B |
|---|---|---|
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| LMArena WebDev | 1582 | — |
| SciCode | 51% | — |
| WeirdML | 66.2% | — |
| LiveBench Coding | — | 10.4% |
| LMArena Coding | 1470 | — |
| ALE-Bench | 1,403 | — |
Agentic & Tool Use Not comparable
DeepSeek V4 Pro: 32.7 (#54), OLMo 2 Furious 13B: —
| Benchmark | DeepSeek V4 Pro | OLMo 2 Furious 13B |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Vending-Bench 2 | 3,285 | — |
Reasoning DeepSeek V4 Pro leads
DeepSeek V4 Pro: 56.4 (#22), OLMo 2 Furious 13B: 14.8 (#312)
| Benchmark | DeepSeek V4 Pro | OLMo 2 Furious 13B |
|---|---|---|
| ARC-AGI-2 | 61.3% | — |
| Kagi LLM Benchmark | 53.5% | — |
| NYT Connections (extended) | 91.3% | — |
| ARC-AGI-1 | 90.5% | — |
| CritPt | 18% | — |
| Chess Puzzles | 47% | — |
| LiveBench Reasoning | — | 16.3% |
| LMArena Hard Prompts | 1461 | — |
| Mystery Game Puzzles | 43% | — |
| DTBench | 93.9% | — |
| LiveBench Data Analysis | — | 20.6% |
| LMCA | 45.5% | — |
| Surface Evolver Bench | 40% | — |
| Epoch Capabilities Index | 155.39 | — |
| ForecastBench | 56.1 | — |
| LiveBench | — | 22.1% |
Math DeepSeek V4 Pro leads
DeepSeek V4 Pro: 64.6 (#24), OLMo 2 Furious 13B: 21.3 (#270)
| Benchmark | DeepSeek V4 Pro | OLMo 2 Furious 13B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| OTIS Mock AIME 2024-2025 | 98.6% | — |
| ProofBench | 50% | — |
| Omni-MATH | — | 15.6% |
| LiveBench Math | — | 13.6% |
| LMArena Math | 1455 | — |
Knowledge DeepSeek V4 Pro leads
DeepSeek V4 Pro: 59.5 (#28), OLMo 2 Furious 13B: 18.0 (#278)
| Benchmark | DeepSeek V4 Pro | OLMo 2 Furious 13B |
|---|---|---|
| GPQA Diamond | 91.7% | — |
| SimpleQA Verified | 52.9% | — |
| MMLU-Pro | — | 31% |
| Vectara Hallucination Rate | 8.6% | — |
| GPQA (HELM) | — | 31.6% |
| LMArena Expert | 1463 | — |
Multilingual Not comparable
DeepSeek V4 Pro: 54.5 (#44), OLMo 2 Furious 13B: —
| Benchmark | DeepSeek V4 Pro | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Non-English | 1438 | — |
| LMArena Chinese | 1486 | — |
| LMArena French | 1473 | — |
| LMArena German | 1458 | — |
| LMArena Japanese | 1448 | — |
| LMArena Korean | 1452 | — |
| LMArena Russian | 1452 | — |
| LMArena Spanish | 1457 | — |
Instruction Following DeepSeek V4 Pro leads
DeepSeek V4 Pro: 76.3 (#44), OLMo 2 Furious 13B: 61.1 (#243)
| Benchmark | DeepSeek V4 Pro | OLMo 2 Furious 13B |
|---|---|---|
| LiveBench Instruction Following | — | 60.6% |
| IFEval | — | 73% |
| LMArena Instruction Following | 1448 | — |
Long Context Not comparable
DeepSeek V4 Pro: 45.0 (#49), OLMo 2 Furious 13B: —
| Benchmark | DeepSeek V4 Pro | OLMo 2 Furious 13B |
|---|---|---|
| CL-bench Life | 13.5% | — |
| LMArena Longer Query | 1459 | — |
Writing & Preference DeepSeek V4 Pro leads
DeepSeek V4 Pro: 65.6 (#45), OLMo 2 Furious 13B: 43.0 (#226)
| Benchmark | DeepSeek V4 Pro | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Text | 1451 | — |
| LMArena Creative Writing | 1446 | — |
| EQ-Bench Creative Writing | 1553 | — |
| WildBench | — | 68.9% |
| EQ-Bench 4 | 1166 | — |
| LMArena Multi-Turn | 1467 | — |
| LiveBench Language | — | 11.2% |
Frequently asked questions
Is DeepSeek V4 Pro better than OLMo 2 Furious 13B?
DeepSeek V4 Pro is the stronger model overall, scoring 54.2 to 29.2 on the Noometry Index.
Is DeepSeek V4 Pro or OLMo 2 Furious 13B better for coding?
DeepSeek V4 Pro scores higher on coding benchmarks: 52.2 versus 28.1 in the Noometry coding category.
How many benchmarks do DeepSeek V4 Pro and OLMo 2 Furious 13B share?
0 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and OLMo 2 Furious 13B has 12.