Model comparison
DeepSeek LLM 67B vs MiniMax-M2.5
MiniMax-M2.5 is the stronger model overall, scoring 38.3 to 24.9 on the Noometry Index.
Last verified . 11 shared benchmarks.
DeepSeek
MiniMaxSummary
- They share 11 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and MiniMax-M2.5 in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where MiniMax-M2.5 leads 39.2 to 7.0.
Side by side
| DeepSeek LLM 67B | MiniMax-M2.5 | |
|---|---|---|
| Provider | DeepSeek | MiniMax |
| Noometry Index | 24.9 | 38.3 |
| Released | 2023-11-29 | 2026-02-12 |
| Weights | Open | Open |
| Context window | — | 205K |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.30 |
| Output $ / M tokens | — | $1.20 |
| Results tracked | 15 | 33 |
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Category by category
Coding MiniMax-M2.5 leads
DeepSeek LLM 67B: 31.9 (#278), MiniMax-M2.5: 48.1 (#58)
| Benchmark | DeepSeek LLM 67B | MiniMax-M2.5 |
|---|---|---|
| LMArena Coding | 1096 | 1381 |
| SWE-bench Verified (bash only) | — | 75.8% |
| LMArena WebDev | — | 1387 |
| SWE-bench Multilingual | — | 68.3% |
| ALE-Bench | — | 618.17 |
Agentic & Tool Use Not comparable
DeepSeek LLM 67B: —, MiniMax-M2.5: 30.4 (#77)
| Benchmark | DeepSeek LLM 67B | MiniMax-M2.5 |
|---|---|---|
| Terminal-Bench | — | 42.7% |
| Vending-Bench 2 | — | -23.16 |
Reasoning Too close to call
DeepSeek LLM 67B: 16.5 (#304), MiniMax-M2.5: 17.5 (#292)
| Benchmark | DeepSeek LLM 67B | MiniMax-M2.5 |
|---|---|---|
| LMArena Hard Prompts | 1070 | 1372 |
| Epoch Capabilities Index | 110.5 | 146.68 |
| ARC-AGI-2 | — | 4.9% |
| Kagi LLM Benchmark | — | 55.2% |
| NYT Connections (extended) | — | 16.8% |
| ARC-AGI-1 | — | 63.7% |
| Chess Puzzles | 0% | — |
Math MiniMax-M2.5 leads
DeepSeek LLM 67B: 8.7 (#324), MiniMax-M2.5: 26.9 (#253)
| Benchmark | DeepSeek LLM 67B | MiniMax-M2.5 |
|---|---|---|
| LMArena Math | 1108 | 1378 |
| OTIS Mock AIME 2024-2025 | 0.8% | — |
| ProofBench | — | 4% |
| MATH Level 5 | 6.4% | — |
Knowledge MiniMax-M2.5 leads
DeepSeek LLM 67B: 7.0 (#313), MiniMax-M2.5: 39.2 (#135)
| Benchmark | DeepSeek LLM 67B | MiniMax-M2.5 |
|---|---|---|
| GPQA Diamond | 24.6% | — |
| Vectara Hallucination Rate | — | 9.1% |
| LMArena Expert | — | 1379 |
Multilingual MiniMax-M2.5 leads
DeepSeek LLM 67B: 29.4 (#267), MiniMax-M2.5: 47.1 (#152)
| Benchmark | DeepSeek LLM 67B | MiniMax-M2.5 |
|---|---|---|
| LMArena Non-English | 1073 | 1338 |
| LMArena Chinese | 1132 | 1393 |
| LMArena French | — | 1362 |
| LMArena German | — | 1362 |
| LMArena Japanese | — | 1171 |
| LMArena Korean | — | 1232 |
| LMArena Russian | — | 1358 |
| LMArena Spanish | — | 1354 |
Instruction Following MiniMax-M2.5 leads
DeepSeek LLM 67B: 55.4 (#277), MiniMax-M2.5: 71.5 (#148)
| Benchmark | DeepSeek LLM 67B | MiniMax-M2.5 |
|---|---|---|
| LMArena Instruction Following | 1079 | 1353 |
Long Context MiniMax-M2.5 leads
DeepSeek LLM 67B: 33.1 (#265), MiniMax-M2.5: 37.5 (#216)
| Benchmark | DeepSeek LLM 67B | MiniMax-M2.5 |
|---|---|---|
| LMArena Longer Query | 1092 | 1366 |
| CL-bench | — | 11.4% |
| CL-bench Life | — | 6.3% |
Writing & Preference MiniMax-M2.5 leads
DeepSeek LLM 67B: 31.6 (#282), MiniMax-M2.5: 53.9 (#153)
| Benchmark | DeepSeek LLM 67B | MiniMax-M2.5 |
|---|---|---|
| LMArena Text | 1105 | 1359 |
| LMArena Creative Writing | 1067 | 1331 |
| LMArena Multi-Turn | 1082 | 1364 |
| EQ-Bench Creative Writing | — | 1361 |
Frequently asked questions
Is DeepSeek LLM 67B better than MiniMax-M2.5?
MiniMax-M2.5 is the stronger model overall, scoring 38.3 to 24.9 on the Noometry Index.
Is DeepSeek LLM 67B or MiniMax-M2.5 better for coding?
MiniMax-M2.5 scores higher on coding benchmarks: 48.1 versus 31.9 in the Noometry coding category.
How many benchmarks do DeepSeek LLM 67B and MiniMax-M2.5 share?
11 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and MiniMax-M2.5 has 33.