Model comparison
DeepSeek-V3.1-Terminus vs MiMo-V2.5
DeepSeek-V3.1-Terminus and MiMo-V2.5 score almost the same on the Noometry Index (43.1 vs 43.4), so choose on price, context window or the category you care about most.
Last verified . 13 shared benchmarks.
DeepSeekSummary
- They share 13 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 2 categories and MiMo-V2.5 in 5 categories; 4 gaps are clear of the uncertainty.
- MiMo-V2.5 is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.27 / $1 for DeepSeek-V3.1-Terminus.
- MiMo-V2.5 accepts more context: 1.05M tokens versus 164K.
Side by side
| DeepSeek-V3.1-Terminus | MiMo-V2.5 | |
|---|---|---|
| Provider | DeepSeek | Xiaomi |
| Noometry Index | 43.1 | 43.4 |
| Released | 2025-09-22 | 2026-04-22 |
| Weights | Open | Open |
| Context window | 164K | 1.05M |
| Max output | 147K | 131K |
| Input $ / M tokens | $0.27 | $0.14 |
| Output $ / M tokens | $1 | $0.28 |
| Results tracked | 16 | 23 |
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Category by category
Coding MiMo-V2.5 leads
DeepSeek-V3.1-Terminus: 42.0 (#113), MiMo-V2.5: 43.9 (#81)
| Benchmark | DeepSeek-V3.1-Terminus | MiMo-V2.5 |
|---|---|---|
| SciCode | 40.6% | 43.1% |
| LMArena Coding | 1426 | 1469 |
| ALE-Bench | 745.17 | 513.95 |
| LMArena WebDev | — | 1438 |
Reasoning MiMo-V2.5 leads
DeepSeek-V3.1-Terminus: 26.4 (#133), MiMo-V2.5: 28.6 (#101)
| Benchmark | DeepSeek-V3.1-Terminus | MiMo-V2.5 |
|---|---|---|
| CritPt | 1.7% | 3.7% |
| LMArena Hard Prompts | 1426 | 1450 |
| Kagi LLM Benchmark | 57.4% | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 38.5 (#137), MiMo-V2.5: 36.8 (#163)
| Benchmark | DeepSeek-V3.1-Terminus | MiMo-V2.5 |
|---|---|---|
| LMArena Math | 1402 | 1436 |
| ProofBench | — | 16% |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, MiMo-V2.5: 40.8 (#115)
| Benchmark | DeepSeek-V3.1-Terminus | MiMo-V2.5 |
|---|---|---|
| LMArena Expert | — | 1460 |
Multimodal Not comparable
DeepSeek-V3.1-Terminus: —, MiMo-V2.5: 39.8 (#54)
| Benchmark | DeepSeek-V3.1-Terminus | MiMo-V2.5 |
|---|---|---|
| LMArena Vision | — | 1247 |
Multilingual Too close to call
DeepSeek-V3.1-Terminus: 52.1 (#92), MiMo-V2.5: 51.9 (#99)
| Benchmark | DeepSeek-V3.1-Terminus | MiMo-V2.5 |
|---|---|---|
| LMArena Non-English | 1407 | 1404 |
| LMArena Russian | 1436 | 1395 |
| LMArena Chinese | — | 1468 |
| LMArena French | — | 1447 |
| LMArena German | — | 1421 |
| LMArena Japanese | — | 1306 |
| LMArena Korean | — | 1363 |
| LMArena Spanish | — | 1416 |
Instruction Following MiMo-V2.5 leads
DeepSeek-V3.1-Terminus: 74.0 (#106), MiMo-V2.5: 75.5 (#60)
| Benchmark | DeepSeek-V3.1-Terminus | MiMo-V2.5 |
|---|---|---|
| LMArena Instruction Following | 1404 | 1434 |
Long Context Too close to call
DeepSeek-V3.1-Terminus: 43.4 (#97), MiMo-V2.5: 44.2 (#73)
| Benchmark | DeepSeek-V3.1-Terminus | MiMo-V2.5 |
|---|---|---|
| LMArena Longer Query | 1421 | 1445 |
Writing & Preference Too close to call
DeepSeek-V3.1-Terminus: 61.0 (#92), MiMo-V2.5: 61.6 (#86)
| Benchmark | DeepSeek-V3.1-Terminus | MiMo-V2.5 |
|---|---|---|
| LMArena Text | 1419 | 1428 |
| LMArena Creative Writing | 1403 | 1393 |
| LMArena Multi-Turn | 1411 | 1445 |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than MiMo-V2.5?
DeepSeek-V3.1-Terminus and MiMo-V2.5 score almost the same on the Noometry Index (43.1 vs 43.4), so choose on price, context window or the category you care about most.
Which is cheaper, DeepSeek-V3.1-Terminus or MiMo-V2.5?
MiMo-V2.5 is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.27 and $1.
Is DeepSeek-V3.1-Terminus or MiMo-V2.5 better for coding?
MiMo-V2.5 scores higher on coding benchmarks: 43.9 versus 42.0 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.5 does, with 1.05M tokens against 164K.
How many benchmarks do DeepSeek-V3.1-Terminus and MiMo-V2.5 share?
13 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and MiMo-V2.5 has 23.