Model comparison
DeepSeek-V3.1-Terminus vs Olmo 3 32b Think
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 38.7 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 32b Think in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.0 to 49.1.
Side by side
| DeepSeek-V3.1-Terminus | Olmo 3 32b Think | |
|---|---|---|
| Provider | DeepSeek | Allen Institute for AI (Ai2) |
| Noometry Index | 43.1 | 38.7 |
| Released | 2025-09-22 | — |
| Weights | Open | Open |
| Context window | 164K | — |
| Max output | 147K | — |
| Input $ / M tokens | $0.27 | — |
| Output $ / M tokens | $1 | — |
| Results tracked | 16 | 14 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 42.0 (#113), Olmo 3 32b Think: 38.6 (#172)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3 32b Think |
|---|---|---|
| LMArena Coding | 1426 | 1319 |
| SciCode | 40.6% | — |
| ALE-Bench | 745.17 | — |
Reasoning Too close to call
DeepSeek-V3.1-Terminus: 26.4 (#133), Olmo 3 32b Think: 25.9 (#140)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3 32b Think |
|---|---|---|
| LMArena Hard Prompts | 1426 | 1302 |
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 38.5 (#137), Olmo 3 32b Think: 36.5 (#165)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3 32b Think |
|---|---|---|
| LMArena Math | 1402 | 1316 |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Olmo 3 32b Think: 35.0 (#190)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3 32b Think |
|---|---|---|
| LMArena Expert | — | 1273 |
Multilingual DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 52.1 (#92), Olmo 3 32b Think: 41.2 (#210)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3 32b Think |
|---|---|---|
| LMArena Non-English | 1407 | 1255 |
| LMArena Russian | 1436 | 1254 |
| LMArena Chinese | — | 1300 |
| LMArena French | — | 1291 |
| LMArena German | — | 1290 |
Instruction Following DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 74.0 (#106), Olmo 3 32b Think: 67.2 (#198)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3 32b Think |
|---|---|---|
| LMArena Instruction Following | 1404 | 1275 |
Long Context DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 43.4 (#97), Olmo 3 32b Think: 39.4 (#182)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3 32b Think |
|---|---|---|
| LMArena Longer Query | 1421 | 1296 |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.0 (#92), Olmo 3 32b Think: 49.1 (#193)
| Benchmark | DeepSeek-V3.1-Terminus | Olmo 3 32b Think |
|---|---|---|
| LMArena Text | 1419 | 1300 |
| LMArena Creative Writing | 1403 | 1256 |
| LMArena Multi-Turn | 1411 | 1290 |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Olmo 3 32b Think?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 38.7 on the Noometry Index.
Is DeepSeek-V3.1-Terminus or Olmo 3 32b Think better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 38.6 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.1-Terminus and Olmo 3 32b Think share?
10 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Olmo 3 32b Think has 14.