Model comparison
DeepSeek-R1-Distill-Llama-70B vs MiMo-V2.6-Flash
MiMo-V2.6-Flash is the stronger model overall, scoring 48.5 to 37.8 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeekSummary
- The widest gap is in coding, where MiMo-V2.6-Flash leads 53.4 to 36.8.
Side by side
| DeepSeek-R1-Distill-Llama-70B | MiMo-V2.6-Flash | |
|---|---|---|
| Provider | DeepSeek | Xiaomi |
| Noometry Index | 37.8 | 48.5 |
| Released | 2025-01-20 | 2026-09-21 |
| Weights | Open | Open |
| Context window | — | 1.05M |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.14 |
| Output $ / M tokens | — | $0.28 |
| Results tracked | 13 | 19 |
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Category by category
Coding MiMo-V2.6-Flash leads
DeepSeek-R1-Distill-Llama-70B: 36.8 (#202), MiMo-V2.6-Flash: 53.4 (#30)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | MiMo-V2.6-Flash |
|---|---|---|
| LMArena WebDev | — | 1637 |
| SciCode | — | 51.3% |
| BigCodeBench Instruct | 35.3% | — |
| LiveBench Coding | 51.6% | — |
| LMArena Coding | — | 1504 |
| BigCodeBench Complete | 49.9% | — |
Reasoning MiMo-V2.6-Flash leads
DeepSeek-R1-Distill-Llama-70B: 24.9 (#156), MiMo-V2.6-Flash: 36.5 (#66)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | MiMo-V2.6-Flash |
|---|---|---|
| Kagi LLM Benchmark | 52.3% | — |
| CritPt | — | 12% |
| LiveBench Reasoning | 67.6% | — |
| LMArena Hard Prompts | — | 1482 |
| LiveBench Data Analysis | 55.9% | — |
| LiveBench | 54.5% | — |
Math MiMo-V2.6-Flash leads
DeepSeek-R1-Distill-Llama-70B: 36.0 (#176), MiMo-V2.6-Flash: 51.9 (#52)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | MiMo-V2.6-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 51.4% | — |
| ProofBench | — | 63% |
| LiveBench Math | 58.1% | — |
| LMArena Math | — | 1468 |
| MATH Level 5 | 89.9% | — |
Knowledge MiMo-V2.6-Flash leads
DeepSeek-R1-Distill-Llama-70B: 30.7 (#225), MiMo-V2.6-Flash: 42.2 (#99)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | MiMo-V2.6-Flash |
|---|---|---|
| GPQA Diamond | 55.7% | — |
| LMArena Expert | — | 1501 |
Multimodal Not comparable
DeepSeek-R1-Distill-Llama-70B: —, MiMo-V2.6-Flash: 40.5 (#47)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Vision | — | 1259 |
Multilingual Not comparable
DeepSeek-R1-Distill-Llama-70B: —, MiMo-V2.6-Flash: 54.0 (#51)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Non-English | — | 1434 |
| LMArena Chinese | — | 1511 |
| LMArena French | — | 1475 |
| LMArena Russian | — | 1409 |
| LMArena Spanish | — | 1456 |
Instruction Following MiMo-V2.6-Flash leads
DeepSeek-R1-Distill-Llama-70B: 68.2 (#190), MiMo-V2.6-Flash: 76.8 (#35)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | MiMo-V2.6-Flash |
|---|---|---|
| LiveBench Instruction Following | 69.9% | — |
| LMArena Instruction Following | — | 1463 |
Long Context Not comparable
DeepSeek-R1-Distill-Llama-70B: —, MiMo-V2.6-Flash: 44.8 (#57)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Longer Query | — | 1463 |
Writing & Preference MiMo-V2.6-Flash leads
DeepSeek-R1-Distill-Llama-70B: 49.0 (#194), MiMo-V2.6-Flash: 63.1 (#67)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Text | — | 1455 |
| LMArena Creative Writing | — | 1400 |
| LMArena Multi-Turn | — | 1451 |
| LiveBench Language | 23.8% | — |
Frequently asked questions
Is DeepSeek-R1-Distill-Llama-70B better than MiMo-V2.6-Flash?
MiMo-V2.6-Flash is the stronger model overall, scoring 48.5 to 37.8 on the Noometry Index.
Is DeepSeek-R1-Distill-Llama-70B or MiMo-V2.6-Flash better for coding?
MiMo-V2.6-Flash scores higher on coding benchmarks: 53.4 versus 36.8 in the Noometry coding category.
How many benchmarks do DeepSeek-R1-Distill-Llama-70B and MiMo-V2.6-Flash share?
0 benchmarks have published results for both models. DeepSeek-R1-Distill-Llama-70B has 13 scored results on Noometry and MiMo-V2.6-Flash has 19.