Model comparison
DeepSeek V4 Pro (High) vs Llama 4 Scout
Head-to-head evidence from 16 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro (High) #81 (Estimated); Llama 4 Scout #174 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro (High) and Llama 4 Scout share 16 comparable benchmark results. 0 of 8 categories are comparable. 22 results are unique to DeepSeek V4 Pro (High); 2 to Llama 4 Scout.
Updated July 23, 2026- Shared results
- 16
- DeepSeek V4 Pro (High) only
- 22
- Llama 4 Scout only
- 2
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek V4 Pro (High) and Llama 4 Scout is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 6 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 (High) 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 (High).
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 (High) | Δ | Llama 4 Scout |
|---|---|---|---|
| Agentic | DeepSeek V4 Pro (High)70.6 | MarginNo overlap | Llama 4 ScoutNot measured |
| Coding | DeepSeek V4 Pro (High)69.8 | MarginNo overlap | Llama 4 ScoutNot measured |
| Knowledge | DeepSeek V4 Pro (High)57.0 | MarginNo overlap | Llama 4 ScoutNot measured |
| Math | DeepSeek V4 Pro (High)94.0 | 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 (High) | Llama 4 Scout | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro (High)$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 Pro (High)Not available | Llama 4 Scout128 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Pro (High)Not available | Llama 4 Scout0.70 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro (High)1M | Llama 4 Scout10M | Llama 4 Scout lists the larger context window. |
Benchmark Deep Dive
Agentic9 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Llama 4 Scout | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 63.3% | — | Not comparable |
| BrowseCompSource | 80.4% | — | Not comparable |
| HLE w/ toolsSource | 44.7% | — | Not comparable |
| MCP AtlasSource | 74.2% | — | Not comparable |
| ToolathlonSource | 49% | — | Not comparable |
| τ²-bench resultsSource | 94.2% | 15.5% | DeepSeek V4 Pro (High) leads |
| GDPval-AASource | 39.9% | 0.0% | DeepSeek V4 Pro (High) leads |
| GDPval-AASource | 1299 | 90 | DeepSeek V4 Pro (High) leads |
| AA Agentic IndexSource | 34.4% | 1.1% | DeepSeek V4 Pro (High) leads |
Coding7 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Llama 4 Scout | Result |
|---|---|---|---|
| CodeforcesSource | 2919.0 | — | Not comparable |
| SWE-bench VerifiedSource | 79.4% | — | Not comparable |
| SWE-bench ProSource | 54.4% | — | Not comparable |
| SWE MultilingualSource | 74.1% | — | Not comparable |
| Terminal-Bench 2.0Source | 63.3% | — | Not comparable |
| AA-SciCodeSource | 46.4% | 17.0% | DeepSeek V4 Pro (High) leads |
| AA Coding IndexSource | 58.7% | 8.2% | DeepSeek V4 Pro (High) leads |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Llama 4 Scout | Result |
|---|---|---|---|
| MMLU-ProSource | 87.1% | — | Not comparable |
| SimpleQASource | 46.2% | — | Not comparable |
| Chinese-SimpleQASource | 77.7% | — | Not comparable |
| GPQASource | 89.1% | — | Not comparable |
| GPQA-DSource | 89.1% | — | Not comparable |
| HLESource | 34.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 43.1% | 10.0% | DeepSeek V4 Pro (High) leads |
| AA-GPQA DiamondSource | 90.5% | 58.7% | DeepSeek V4 Pro (High) leads |
| AA-HLESource | 33.5% | 4.3% | DeepSeek V4 Pro (High) leads |
| AA-Omniscience IndexSource | -9.7% | -52.4% | DeepSeek V4 Pro (High) leads |
| AA-Omniscience AccuracySource | 41.8% | 14.6% | DeepSeek V4 Pro (High) leads |
| AA-Omniscience Hallucination RateSource | 88.6% | 78.3% | Llama 4 Scout leads |
Math5 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Llama 4 Scout | Result |
|---|---|---|---|
| AA-IFBenchSource | 71.3% | 39.5% | DeepSeek V4 Pro (High) leads |
Frequently Asked Questions (3)
Can I compare DeepSeek V4 Pro (High) 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 (High) and Llama 4 Scout today?
DeepSeek V4 Pro (High): $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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