Model comparison
DeepSeek-V3.1-Terminus vs Olmo 3.1 32b Instruct
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 38.8 on the Noometry Index.
Last verified . 10 shared benchmarks.
DeepSeek
Allen Institute for AI (Ai2)Summary
- They share 10 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 7 categories and Olmo 3.1 32b Instruct in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.3 to 50.4.
Side by side
| DeepSeek-V3.1-Terminus | Olmo 3.1 32b Instruct | |
|---|---|---|
| Provider | DeepSeek | Allen Institute for AI (Ai2) |
| Noometry Index | 42.6 | 38.8 |
| Released | 2025-09-22 | — |
| Weights | Open | Open |
| Context window | 164K | — |
| Max output | 66K | — |
| Input $ / M tokens | $0.30 | — |
| Output $ / M tokens | $1 | — |
| Results tracked | 16 | 16 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 41.5 (#114), Olmo 3.1 32b Instruct: 38.9 (#154)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3.1 32b Instruct |
|---|---|---|
| LMArena Coding | 1426 | 1346 |
| SciCode | 40.6% | — |
| ALE-Bench | 745.17 | — |
Reasoning Too close to call
DeepSeek-V3.1-Terminus: 25.7 (#126), Olmo 3.1 32b Instruct: 25.4 (#131)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3.1 32b Instruct |
|---|---|---|
| LMArena Hard Prompts | 1427 | 1322 |
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 35.7 (#138), Olmo 3.1 32b Instruct: 33.6 (#169)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3.1 32b Instruct |
|---|---|---|
| LMArena Math | 1402 | 1305 |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Olmo 3.1 32b Instruct: 35.4 (#175)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3.1 32b Instruct |
|---|---|---|
| LMArena Expert | — | 1307 |
Multilingual DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 52.3 (#87), Olmo 3.1 32b Instruct: 42.8 (#185)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3.1 32b Instruct |
|---|---|---|
| LMArena Non-English | 1407 | 1275 |
| LMArena Russian | 1434 | 1268 |
| LMArena Chinese | — | 1304 |
| LMArena French | — | 1328 |
| LMArena German | — | 1283 |
| LMArena Korean | — | 1206 |
| LMArena Spanish | — | 1337 |
Instruction Following DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 74.4 (#96), Olmo 3.1 32b Instruct: 68.8 (#182)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3.1 32b Instruct |
|---|---|---|
| LMArena Instruction Following | 1406 | 1298 |
Long Context DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 43.5 (#88), Olmo 3.1 32b Instruct: 39.9 (#161)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3.1 32b Instruct |
|---|---|---|
| LMArena Longer Query | 1426 | 1312 |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.3 (#87), Olmo 3.1 32b Instruct: 50.4 (#179)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3.1 32b Instruct |
|---|---|---|
| LMArena Text | 1420 | 1311 |
| LMArena Creative Writing | 1404 | 1264 |
| LMArena Multi-Turn | 1411 | 1309 |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Olmo 3.1 32b Instruct?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 38.8 on the Noometry Index.
Is DeepSeek-V3.1-Terminus or Olmo 3.1 32b Instruct better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 41.5 versus 38.9 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.1-Terminus and Olmo 3.1 32b Instruct share?
10 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Olmo 3.1 32b Instruct has 16.