Model comparison
Claude 4 Sonnet vs Llama 3.1 405B
Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude 4 Sonnet #158 (Supported); Llama 3.1 405B #102 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude 4 Sonnet and Llama 3.1 405B share 11 comparable benchmark results. 0 of 8 categories are comparable. 5 results are unique to Claude 4 Sonnet; 0 to Llama 3.1 405B.
Updated July 20, 2026- Shared results
- 11
- Claude 4 Sonnet only
- 5
- Llama 3.1 405B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Claude 4 Sonnet and Llama 3.1 405B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 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.
Claude 4 Sonnet is priced at $3.00 input / $15.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Llama 3.1 405B. Claude 4 Sonnet has the larger context window at 200K, compared with 128K for Llama 3.1 405B.
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 | Claude 4 Sonnet | Δ | Llama 3.1 405B |
|---|---|---|---|
| Coding | Claude 4 Sonnet72.7 | MarginNo overlap | Llama 3.1 405BNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude 4 Sonnet | Llama 3.1 405B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude 4 Sonnet$3 input / $15 output | Llama 3.1 405B$0 input / $0 output | Llama 3.1 405B has the lower combined listed price. |
| Generation speedtokens per second | Claude 4 Sonnet40 tok/s | Llama 3.1 405B29 tok/s | Claude 4 Sonnet has the higher measured throughput. |
| First-answer latencyseconds to first token | Claude 4 Sonnet1.33 s | Llama 3.1 405B2.19 s | Claude 4 Sonnet reaches the first token sooner. |
| Context windowmaximum listed tokens | Claude 4 Sonnet200K | Llama 3.1 405B128K | Claude 4 Sonnet lists the larger context window. |
Benchmark Deep Dive
Agentic3 benchmarks
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Claude 4 Sonnet | Llama 3.1 405B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 25.5% | 8.5% | Claude 4 Sonnet leads |
| AA-GPQA DiamondSource | 68.3% | 51.5% | Claude 4 Sonnet leads |
| AA-HLESource | 4.0% | 4.2% | Llama 3.1 405B leads |
| AA-Omniscience IndexSource | -9.2% | -17.3% | Claude 4 Sonnet leads |
| AA-Omniscience AccuracySource | 22.4% | 22.3% | Claude 4 Sonnet leads |
| AA-Omniscience Hallucination RateSource | 40.8% | 51.0% | Claude 4 Sonnet leads |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude 4 Sonnet | Llama 3.1 405B | Result |
|---|---|---|---|
| AA-IFBenchSource | 45.4% | 39.0% | Claude 4 Sonnet leads |
Frequently Asked Questions (3)
Can I compare Claude 4 Sonnet 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 Claude 4 Sonnet and Llama 3.1 405B today?
Claude 4 Sonnet: $3.00 input / $15.00 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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