Model comparison
DeepSeek V4 Pro vs Llama 4 Scout
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro #46 (Supported); Llama 4 Scout #174 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro and Llama 4 Scout share 1 comparable benchmark result. 0 of 8 categories are comparable. 22 results are unique to DeepSeek V4 Pro; 17 to Llama 4 Scout.
Updated July 23, 2026- Shared results
- 1
- DeepSeek V4 Pro only
- 22
- Llama 4 Scout only
- 17
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek V4 Pro and Llama 4 Scout is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 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 4 Scout. Llama 4 Scout has the larger context window at 10M, compared with 1M for DeepSeek V4 Pro.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | DeepSeek V4 Pro | Δ | Llama 4 Scout |
|---|---|---|---|
| Agentic | DeepSeek V4 Pro59.1 | MarginNo overlap | Llama 4 ScoutNot measured |
| Coding | DeepSeek V4 Pro65.3 | MarginNo overlap | Llama 4 ScoutNot measured |
| Knowledge | DeepSeek V4 Pro41.3 | MarginNo overlap | Llama 4 ScoutNot measured |
| Math | DeepSeek V4 Pro31.7 | MarginNo overlap | Llama 4 ScoutNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro | Llama 4 Scout | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro$0.435 input / $0.87 output | Llama 4 Scout$0 input / $0 output | Llama 4 Scout has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 ProNot available | Llama 4 Scout128 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 ProNot available | Llama 4 Scout0.70 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro1M | Llama 4 Scout10M | Llama 4 Scout lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | DeepSeek V4 Pro | Llama 4 Scout | 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 |
| AA Agentic IndexSource | — | 1.1% | Not comparable |
| τ²-bench resultsSource | — | 15.5% | Not comparable |
| GDPval-AASource | — | 0.0% | Not comparable |
| GDPval-AASource | — | 90 | Not comparable |
Coding6 benchmarks
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | DeepSeek V4 Pro | Llama 4 Scout | 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 | — | 10.0% | Not comparable |
| AA-GPQA DiamondSource | — | 58.7% | Not comparable |
| AA-HLESource | — | 4.3% | Not comparable |
| AA-Omniscience IndexSource | — | -52.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 14.6% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 78.3% | Not comparable |
Math5 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro | Llama 4 Scout | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 39.5% | Not comparable |
Frequently Asked Questions (3)
Can I compare DeepSeek V4 Pro and Llama 4 Scout 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 4 Scout today?
DeepSeek V4 Pro: $0.43 input / $0.87 output per 1M tokens Llama 4 Scout: $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.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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