Model comparison
DeepSeek-V3.1-Terminus vs OLMo 2 Furious 13B
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 29.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Allen Institute for AI (Ai2)Summary
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.0 to 42.9.
Side by side
| DeepSeek-V3.1-Terminus | OLMo 2 Furious 13B | |
|---|---|---|
| Provider | DeepSeek | Allen Institute for AI (Ai2) |
| Noometry Index | 43.1 | 29.7 |
| Released | 2025-09-22 | 2024-12-31 |
| Weights | Open | Open |
| Context window | 164K | — |
| Max output | 147K | — |
| Input $ / M tokens | $0.27 | — |
| Output $ / M tokens | $1 | — |
| Results tracked | 16 | 12 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 42.0 (#113), OLMo 2 Furious 13B: 28.6 (#313)
| Benchmark | DeepSeek-V3.1-Terminus | OLMo 2 Furious 13B |
|---|---|---|
| SciCode | 40.6% | — |
| LiveBench Coding | — | 10.4% |
| LMArena Coding | 1426 | — |
| ALE-Bench | 745.17 | — |
Reasoning DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 26.4 (#133), OLMo 2 Furious 13B: 15.5 (#314)
| Benchmark | DeepSeek-V3.1-Terminus | OLMo 2 Furious 13B |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| LiveBench Reasoning | — | 16.3% |
| LMArena Hard Prompts | 1426 | — |
| DTBench | 81.3% | — |
| LiveBench Data Analysis | — | 20.6% |
| LMCA | 28.6% | — |
| LiveBench | — | 22.1% |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 38.5 (#137), OLMo 2 Furious 13B: 23.1 (#273)
| Benchmark | DeepSeek-V3.1-Terminus | OLMo 2 Furious 13B |
|---|---|---|
| Omni-MATH | — | 15.6% |
| LiveBench Math | — | 13.6% |
| LMArena Math | 1402 | — |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, OLMo 2 Furious 13B: 18.3 (#283)
| Benchmark | DeepSeek-V3.1-Terminus | OLMo 2 Furious 13B |
|---|---|---|
| MMLU-Pro | — | 31% |
| GPQA (HELM) | — | 31.6% |
Multilingual Not comparable
DeepSeek-V3.1-Terminus: 52.1 (#92), OLMo 2 Furious 13B: —
| Benchmark | DeepSeek-V3.1-Terminus | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1436 | — |
Instruction Following DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 74.0 (#106), OLMo 2 Furious 13B: 60.9 (#248)
| Benchmark | DeepSeek-V3.1-Terminus | OLMo 2 Furious 13B |
|---|---|---|
| LiveBench Instruction Following | — | 60.6% |
| IFEval | — | 73% |
| LMArena Instruction Following | 1404 | — |
Long Context Not comparable
DeepSeek-V3.1-Terminus: 43.4 (#97), OLMo 2 Furious 13B: —
| Benchmark | DeepSeek-V3.1-Terminus | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Longer Query | 1421 | — |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.0 (#92), OLMo 2 Furious 13B: 42.9 (#230)
| Benchmark | DeepSeek-V3.1-Terminus | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Text | 1419 | — |
| LMArena Creative Writing | 1403 | — |
| WildBench | — | 68.9% |
| LMArena Multi-Turn | 1411 | — |
| LiveBench Language | — | 11.2% |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than OLMo 2 Furious 13B?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 29.7 on the Noometry Index.
Is DeepSeek-V3.1-Terminus or OLMo 2 Furious 13B better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 28.6 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.1-Terminus and OLMo 2 Furious 13B share?
0 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and OLMo 2 Furious 13B has 12.