Model comparison
DeepSeek-V2.5 (Sep 2024) vs Laguna M.1
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.0 to 31.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
PoolsideSummary
- The widest gap is in math, where DeepSeek-V2.5 (Sep 2024) leads 33.3 to 20.3.
Side by side
| DeepSeek-V2.5 (Sep 2024) | Laguna M.1 | |
|---|---|---|
| Provider | DeepSeek | Poolside |
| Noometry Index | 37.0 | 31.9 |
| Released | 2024-09-06 | 2026-04-28 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 33K |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 22 | 3 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Laguna M.1 leads
DeepSeek-V2.5 (Sep 2024): 31.3 (#274), Laguna M.1: 36.4 (#195)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Laguna M.1 |
|---|---|---|
| Aider Polyglot | 17.8% | — |
| LMArena WebDev | — | 1348 |
| BigCodeBench Instruct | 48.6% | — |
| 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), Laguna M.1: 21.9 (#187)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Laguna M.1 |
|---|---|---|
| LMArena Hard Prompts | 1289 | — |
| Surface Evolver Bench | — | 15.6% |
Math DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 33.3 (#177), Laguna M.1: 20.3 (#276)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Laguna M.1 |
|---|---|---|
| ProofBench | — | 0% |
| LMArena Math | 1289 | — |
Knowledge Not comparable
DeepSeek-V2.5 (Sep 2024): 34.2 (#190), Laguna M.1: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Laguna M.1 |
|---|---|---|
| LMArena Expert | 1266 | — |
Multilingual Not comparable
DeepSeek-V2.5 (Sep 2024): 42.7 (#188), Laguna M.1: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Laguna M.1 |
|---|---|---|
| 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 Not comparable
DeepSeek-V2.5 (Sep 2024): 67.7 (#189), Laguna M.1: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Laguna M.1 |
|---|---|---|
| LMArena Instruction Following | 1280 | — |
Long Context Not comparable
DeepSeek-V2.5 (Sep 2024): 39.5 (#169), Laguna M.1: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Laguna M.1 |
|---|---|---|
| LMArena Longer Query | 1301 | — |
Writing & Preference Not comparable
DeepSeek-V2.5 (Sep 2024): 50.0 (#182), Laguna M.1: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Laguna M.1 |
|---|---|---|
| LMArena Text | 1294 | — |
| LMArena Creative Writing | 1285 | — |
| LMArena Multi-Turn | 1297 | — |
Frequently asked questions
Is DeepSeek-V2.5 (Sep 2024) better than Laguna M.1?
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.0 to 31.9 on the Noometry Index.
Is DeepSeek-V2.5 (Sep 2024) or Laguna M.1 better for coding?
Laguna M.1 scores higher on coding benchmarks: 36.4 versus 31.3 in the Noometry coding category.
How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Laguna M.1 share?
0 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Laguna M.1 has 3.