Model comparison
DeepSeek V4 Pro vs Llama 3.1 405B
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro #46 (Supported); Llama 3.1 405B #102 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro and Llama 3.1 405B share 0 comparable benchmark results. 0 of 8 categories are comparable. 23 results are unique to DeepSeek V4 Pro; 11 to Llama 3.1 405B.
Updated July 23, 2026- Shared results
- 0
- DeepSeek V4 Pro only
- 23
- Llama 3.1 405B only
- 11
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek V4 Pro and Llama 3.1 405B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
DeepSeek V4 Pro is priced at $0.43 input / $0.87 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Llama 3.1 405B. DeepSeek V4 Pro has the larger context window at 1M, compared with 128K for Llama 3.1 405B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro | Llama 3.1 405B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro$0.435 input / $0.87 output | Llama 3.1 405B$0 input / $0 output | Llama 3.1 405B has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 ProNot available | Llama 3.1 405B29 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 ProNot available | Llama 3.1 405B2.19 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro1M | Llama 3.1 405B128K | DeepSeek V4 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic7 benchmarks
| Benchmark | DeepSeek V4 Pro | Llama 3.1 405B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.1% | — | Not comparable |
| MCP AtlasSource | 69.4% | — | Not comparable |
| ToolathlonSource | 46.3% | — | Not comparable |
| Claw-EvalSource | 59.8% | — | Not comparable |
| Gert LabsSource | 50.28% | — | Not comparable |
| ResearchClawBenchSource | 17.1% | — | Not comparable |
| τ²-bench resultsSource | — | 19% | Not comparable |
Coding5 benchmarks
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | DeepSeek V4 Pro | Llama 3.1 405B | Result |
|---|---|---|---|
| MMLU-ProSource | 82.9% | — | Not comparable |
| SimpleQASource | 45% | — | Not comparable |
| Chinese-SimpleQASource | 75.8% | — | Not comparable |
| GPQASource | 72.9% | — | Not comparable |
| GPQA-DSource | 72.9% | — | Not comparable |
| HLESource | 7.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 8.5% | Not comparable |
| AA-GPQA DiamondSource | — | 51.5% | Not comparable |
| AA-HLESource | — | 4.2% | Not comparable |
| AA-Omniscience IndexSource | — | -17.3% | Not comparable |
| AA-Omniscience AccuracySource | — | 22.3% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 51.0% | Not comparable |
Math4 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V4 Pro | Llama 3.1 405B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1264 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro | Llama 3.1 405B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 39.0% | Not comparable |
Frequently Asked Questions (3)
Can I compare DeepSeek V4 Pro and Llama 3.1 405B on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for DeepSeek V4 Pro and Llama 3.1 405B today?
DeepSeek V4 Pro: $0.43 input / $0.87 output per 1M tokens Llama 3.1 405B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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