Model comparison
DeepSeek V4.1 Flash vs Llama2 70b Steerlm Chat
DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 31.2 on the Noometry Index.
Last verified . 9 shared benchmarks.
DeepSeek
NVIDIASummary
- They share 9 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 7 categories and Llama2 70b Steerlm Chat in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek V4.1 Flash leads 65.8 to 31.8.
Side by side
| DeepSeek V4.1 Flash | Llama2 70b Steerlm Chat | |
|---|---|---|
| Provider | DeepSeek | NVIDIA |
| Noometry Index | 50.3 | 31.2 |
| Released | 2026-09-09 | — |
| Weights | Open | Open |
| Context window | 1M | — |
| Max output | 393K | — |
| Input $ / M tokens | $0.15 | — |
| Output $ / M tokens | $0.60 | — |
| Results tracked | 25 | 9 |
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Category by category
Coding DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 52.8 (#29), Llama2 70b Steerlm Chat: 29.3 (#295)
| Benchmark | DeepSeek V4.1 Flash | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Coding | 1511 | 1025 |
| LMArena WebDev | 1620 | — |
| SciCode | 51.9% | — |
| ALE-Bench | 1,092 | — |
Reasoning DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 46.2 (#39), Llama2 70b Steerlm Chat: 19.1 (#245)
| Benchmark | DeepSeek V4.1 Flash | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Hard Prompts | 1485 | 1047 |
| NYT Connections (extended) | 89.6% | — |
| CritPt | 14.3% | — |
| DTBench | 89.9% | — |
| LMCA | 47% | — |
| Surface Evolver Bench | 46.3% | — |
| Epoch Capabilities Index | 155.01 | — |
Math DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 48.4 (#52), Llama2 70b Steerlm Chat: 28.8 (#223)
| Benchmark | DeepSeek V4.1 Flash | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Math | 1493 | 1072 |
| ProofBench | 54% | — |
Knowledge Not comparable
DeepSeek V4.1 Flash: 41.6 (#97), Llama2 70b Steerlm Chat: —
| Benchmark | DeepSeek V4.1 Flash | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Expert | 1505 | — |
Multilingual DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 55.5 (#29), Llama2 70b Steerlm Chat: 28.9 (#265)
| Benchmark | DeepSeek V4.1 Flash | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Non-English | 1452 | 1064 |
| LMArena Chinese | 1506 | — |
| LMArena French | 1448 | — |
| LMArena Russian | 1473 | — |
| LMArena Spanish | 1499 | — |
Instruction Following DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 77.6 (#24), Llama2 70b Steerlm Chat: 54.5 (#274)
| Benchmark | DeepSeek V4.1 Flash | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Instruction Following | 1475 | 1061 |
Long Context DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 45.2 (#46), Llama2 70b Steerlm Chat: 30.4 (#283)
| Benchmark | DeepSeek V4.1 Flash | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Longer Query | 1476 | 998 |
Writing & Preference DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 65.8 (#43), Llama2 70b Steerlm Chat: 31.8 (#278)
| Benchmark | DeepSeek V4.1 Flash | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Text | 1465 | 1098 |
| LMArena Creative Writing | 1436 | 1091 |
| LMArena Multi-Turn | 1460 | 1058 |
| EQ-Bench Creative Writing | 1540 | — |
Frequently asked questions
Is DeepSeek V4.1 Flash better than Llama2 70b Steerlm Chat?
DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 31.2 on the Noometry Index.
Is DeepSeek V4.1 Flash or Llama2 70b Steerlm Chat better for coding?
DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.8 versus 29.3 in the Noometry coding category.
How many benchmarks do DeepSeek V4.1 Flash and Llama2 70b Steerlm Chat share?
9 benchmarks have published results for both models. DeepSeek V4.1 Flash has 25 scored results on Noometry and Llama2 70b Steerlm Chat has 9.