Model comparison
DeepSeek V4.1 Flash vs MiniMax-M2.5
DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 38.1 on the Noometry Index.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 8 categories and MiniMax-M2.5 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4.1 Flash leads 46.2 to 17.6.
- The biggest single-benchmark swing is NYT Connections (extended): 89.6% for DeepSeek V4.1 Flash and 16.8% for MiniMax-M2.5.
- DeepSeek V4.1 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.5.
- DeepSeek V4.1 Flash accepts more context: 1M tokens versus 205K.
Side by side
| DeepSeek V4.1 Flash | MiniMax-M2.5 | |
|---|---|---|
| Provider | DeepSeek | MiniMax |
| Noometry Index | 50.3 | 38.1 |
| Released | 2026-09-09 | 2026-02-12 |
| Weights | Open | Open |
| Context window | 1M | 205K |
| Max output | 393K | 131K |
| Input $ / M tokens | $0.15 | $0.30 |
| Output $ / M tokens | $0.60 | $1.20 |
| Results tracked | 25 | 33 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 52.8 (#29), MiniMax-M2.5: 47.9 (#53)
| Benchmark | DeepSeek V4.1 Flash | MiniMax-M2.5 |
|---|---|---|
| LMArena WebDev | 1620 | 1386 |
| LMArena Coding | 1511 | 1380 |
| ALE-Bench | 1,092 | 618.17 |
| SWE-bench Verified (bash only) | — | 75.8% |
| SWE-bench Multilingual | — | 68.3% |
| SciCode | 51.9% | — |
Agentic & Tool Use Not comparable
DeepSeek V4.1 Flash: —, MiniMax-M2.5: 30.2 (#70)
| Benchmark | DeepSeek V4.1 Flash | MiniMax-M2.5 |
|---|---|---|
| Terminal-Bench | — | 42.7% |
| Vending-Bench 2 | — | -23.16 |
Reasoning DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 46.2 (#39), MiniMax-M2.5: 17.6 (#281)
| Benchmark | DeepSeek V4.1 Flash | MiniMax-M2.5 |
|---|---|---|
| NYT Connections (extended) | 89.6% | 16.8% |
| LMArena Hard Prompts | 1485 | 1372 |
| Epoch Capabilities Index | 155.01 | 146.68 |
| ARC-AGI-2 | — | 4.9% |
| Kagi LLM Benchmark | — | 55.2% |
| ARC-AGI-1 | — | 63.7% |
| CritPt | 14.3% | — |
| DTBench | 89.9% | — |
| LMCA | 47% | — |
| Surface Evolver Bench | 46.3% | — |
Math DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 48.4 (#52), MiniMax-M2.5: 25.8 (#242)
| Benchmark | DeepSeek V4.1 Flash | MiniMax-M2.5 |
|---|---|---|
| ProofBench | 54% | 4% |
| LMArena Math | 1493 | 1378 |
Knowledge DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 41.6 (#97), MiniMax-M2.5: 38.6 (#132)
| Benchmark | DeepSeek V4.1 Flash | MiniMax-M2.5 |
|---|---|---|
| LMArena Expert | 1505 | 1378 |
| Vectara Hallucination Rate | — | 9.1% |
Multilingual DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 55.5 (#29), MiniMax-M2.5: 47.3 (#147)
| Benchmark | DeepSeek V4.1 Flash | MiniMax-M2.5 |
|---|---|---|
| LMArena Non-English | 1452 | 1338 |
| LMArena Chinese | 1506 | 1392 |
| LMArena French | 1448 | 1363 |
| LMArena Russian | 1473 | 1359 |
| LMArena Spanish | 1499 | 1354 |
| LMArena German | — | 1361 |
| LMArena Japanese | — | 1169 |
| LMArena Korean | — | 1232 |
Instruction Following DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 77.6 (#24), MiniMax-M2.5: 71.7 (#143)
| Benchmark | DeepSeek V4.1 Flash | MiniMax-M2.5 |
|---|---|---|
| LMArena Instruction Following | 1475 | 1353 |
Long Context DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 45.2 (#46), MiniMax-M2.5: 37.4 (#211)
| Benchmark | DeepSeek V4.1 Flash | MiniMax-M2.5 |
|---|---|---|
| LMArena Longer Query | 1476 | 1367 |
| CL-bench | — | 11.4% |
| CL-bench Life | — | 6.3% |
Writing & Preference DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 65.8 (#43), MiniMax-M2.5: 54.1 (#149)
| Benchmark | DeepSeek V4.1 Flash | MiniMax-M2.5 |
|---|---|---|
| LMArena Text | 1465 | 1359 |
| LMArena Creative Writing | 1436 | 1331 |
| EQ-Bench Creative Writing | 1540 | 1361 |
| LMArena Multi-Turn | 1460 | 1364 |
Frequently asked questions
Is DeepSeek V4.1 Flash better than MiniMax-M2.5?
DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 38.1 on the Noometry Index.
Which is cheaper, DeepSeek V4.1 Flash or MiniMax-M2.5?
DeepSeek V4.1 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; MiniMax-M2.5 lists at $0.30 and $1.20.
Is DeepSeek V4.1 Flash or MiniMax-M2.5 better for coding?
DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.8 versus 47.9 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4.1 Flash does, with 1M tokens against 205K.
How many benchmarks do DeepSeek V4.1 Flash and MiniMax-M2.5 share?
20 benchmarks have published results for both models. DeepSeek V4.1 Flash has 25 scored results on Noometry and MiniMax-M2.5 has 33.