Model comparison
DeepSeek-V2.5 (Sep 2024) vs OLMo 2 Furious 13B
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.0 to 29.2 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Allen Institute for AI (Ai2)Summary
- The widest gap is in knowledge, where DeepSeek-V2.5 (Sep 2024) leads 34.2 to 18.0.
Side by side
| DeepSeek-V2.5 (Sep 2024) | OLMo 2 Furious 13B | |
|---|---|---|
| Provider | DeepSeek | Allen Institute for AI (Ai2) |
| Noometry Index | 37.0 | 29.2 |
| Released | 2024-09-06 | 2024-12-31 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 22 | 12 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 31.3 (#274), OLMo 2 Furious 13B: 28.1 (#309)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | OLMo 2 Furious 13B |
|---|---|---|
| Aider Polyglot | 17.8% | — |
| BigCodeBench Instruct | 48.6% | — |
| LiveBench Coding | — | 10.4% |
| LMArena Coding | 1310 | — |
| BigCodeBench Complete | 53.2% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |
Reasoning DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 24.5 (#145), OLMo 2 Furious 13B: 14.8 (#312)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | OLMo 2 Furious 13B |
|---|---|---|
| LiveBench Reasoning | — | 16.3% |
| LMArena Hard Prompts | 1289 | — |
| LiveBench Data Analysis | — | 20.6% |
| LiveBench | — | 22.1% |
Math DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 33.3 (#177), OLMo 2 Furious 13B: 21.3 (#270)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | OLMo 2 Furious 13B |
|---|---|---|
| Omni-MATH | — | 15.6% |
| LiveBench Math | — | 13.6% |
| LMArena Math | 1289 | — |
Knowledge DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 34.2 (#190), OLMo 2 Furious 13B: 18.0 (#278)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | OLMo 2 Furious 13B |
|---|---|---|
| MMLU-Pro | — | 31% |
| GPQA (HELM) | — | 31.6% |
| LMArena Expert | 1266 | — |
Multilingual Not comparable
DeepSeek-V2.5 (Sep 2024): 42.7 (#188), OLMo 2 Furious 13B: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Non-English | 1273 | — |
| LMArena Chinese | 1317 | — |
| LMArena French | 1288 | — |
| LMArena German | 1258 | — |
| LMArena Japanese | 1228 | — |
| LMArena Korean | 1209 | — |
| LMArena Russian | 1289 | — |
| LMArena Spanish | 1248 | — |
Instruction Following DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 67.7 (#189), OLMo 2 Furious 13B: 61.1 (#243)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | OLMo 2 Furious 13B |
|---|---|---|
| LiveBench Instruction Following | — | 60.6% |
| IFEval | — | 73% |
| LMArena Instruction Following | 1280 | — |
Long Context Not comparable
DeepSeek-V2.5 (Sep 2024): 39.5 (#169), OLMo 2 Furious 13B: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Longer Query | 1301 | — |
Writing & Preference DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 50.0 (#182), OLMo 2 Furious 13B: 43.0 (#226)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Text | 1294 | — |
| LMArena Creative Writing | 1285 | — |
| WildBench | — | 68.9% |
| LMArena Multi-Turn | 1297 | — |
| LiveBench Language | — | 11.2% |
Frequently asked questions
Is DeepSeek-V2.5 (Sep 2024) better than OLMo 2 Furious 13B?
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.0 to 29.2 on the Noometry Index.
Is DeepSeek-V2.5 (Sep 2024) or OLMo 2 Furious 13B better for coding?
DeepSeek-V2.5 (Sep 2024) scores higher on coding benchmarks: 31.3 versus 28.1 in the Noometry coding category.
How many benchmarks do DeepSeek-V2.5 (Sep 2024) and OLMo 2 Furious 13B share?
0 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and OLMo 2 Furious 13B has 12.