Model comparison
DeepSeek-V3.1-Terminus vs Laguna M.1
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 31.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
PoolsideSummary
- The widest gap is in math, where DeepSeek-V3.1-Terminus leads 35.7 to 20.3.
- Laguna M.1 accepts more context: 262K tokens versus 164K.
Side by side
| DeepSeek-V3.1-Terminus | Laguna M.1 | |
|---|---|---|
| Provider | DeepSeek | Poolside |
| Noometry Index | 42.6 | 31.9 |
| Released | 2025-09-22 | 2026-04-28 |
| Weights | Open | Open |
| Context window | 164K | 262K |
| Max output | 66K | 33K |
| Input $ / M tokens | $0.30 | — |
| Output $ / M tokens | $1 | — |
| Results tracked | 16 | 3 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 41.5 (#114), Laguna M.1: 36.4 (#195)
| Benchmark | DeepSeek-V3.1-Terminus | Laguna M.1 |
|---|---|---|
| LMArena WebDev | — | 1348 |
| SciCode | 40.6% | — |
| LMArena Coding | 1426 | — |
| ALE-Bench | 745.17 | — |
Reasoning DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 25.7 (#126), Laguna M.1: 21.9 (#187)
| Benchmark | DeepSeek-V3.1-Terminus | Laguna M.1 |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| LMArena Hard Prompts | 1427 | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
| Surface Evolver Bench | — | 15.6% |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 35.7 (#138), Laguna M.1: 20.3 (#276)
| Benchmark | DeepSeek-V3.1-Terminus | Laguna M.1 |
|---|---|---|
| ProofBench | — | 0% |
| LMArena Math | 1402 | — |
Multilingual Not comparable
DeepSeek-V3.1-Terminus: 52.3 (#87), Laguna M.1: —
| Benchmark | DeepSeek-V3.1-Terminus | Laguna M.1 |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1434 | — |
Instruction Following Not comparable
DeepSeek-V3.1-Terminus: 74.4 (#96), Laguna M.1: —
| Benchmark | DeepSeek-V3.1-Terminus | Laguna M.1 |
|---|---|---|
| LMArena Instruction Following | 1406 | — |
Long Context Not comparable
DeepSeek-V3.1-Terminus: 43.5 (#88), Laguna M.1: —
| Benchmark | DeepSeek-V3.1-Terminus | Laguna M.1 |
|---|---|---|
| LMArena Longer Query | 1426 | — |
Writing & Preference Not comparable
DeepSeek-V3.1-Terminus: 61.3 (#87), Laguna M.1: —
| Benchmark | DeepSeek-V3.1-Terminus | Laguna M.1 |
|---|---|---|
| LMArena Text | 1420 | — |
| LMArena Creative Writing | 1404 | — |
| LMArena Multi-Turn | 1411 | — |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Laguna M.1?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 31.9 on the Noometry Index.
Is DeepSeek-V3.1-Terminus or Laguna M.1 better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 41.5 versus 36.4 in the Noometry coding category.
Which has the bigger context window?
Laguna M.1 does, with 262K tokens against 164K.
How many benchmarks do DeepSeek-V3.1-Terminus and Laguna M.1 share?
0 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Laguna M.1 has 3.