Model comparison
DeepSeek V3.2 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: DeepSeek V3.2 #82 (Supported); Llama 3.1 405B #102 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 and Llama 3.1 405B share 11 comparable benchmark results. 0 of 8 categories are comparable. 8 results are unique to DeepSeek V3.2; 0 to Llama 3.1 405B.
Updated July 20, 2026- Shared results
- 11
- DeepSeek V3.2 only
- 8
- Llama 3.1 405B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek V3.2 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.
DeepSeek V3.2 is priced at $0.28 input / $0.42 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens 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 | DeepSeek V3.2 | Δ | Llama 3.1 405B |
|---|---|---|---|
| Coding | DeepSeek V3.260.9 | MarginNo overlap | Llama 3.1 405BNot measured |
| Math | DeepSeek V3.217.1 | 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 | DeepSeek V3.2 | Llama 3.1 405B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2$0.28 input / $0.42 output | Llama 3.1 405B$0 input / $0 output | Llama 3.1 405B has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V3.235 tok/s | Llama 3.1 405B29 tok/s | DeepSeek V3.2 has the higher measured throughput. |
| First-answer latencyseconds to first token | DeepSeek V3.23.75 s | Llama 3.1 405B2.19 s | Llama 3.1 405B reaches the first token sooner. |
| Context windowmaximum listed tokens | DeepSeek V3.2128K | Llama 3.1 405B128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | DeepSeek V3.2 | Llama 3.1 405B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | 8.5% | DeepSeek V3.2 leads |
| AA-GPQA DiamondSource | 75.1% | 51.5% | DeepSeek V3.2 leads |
| AA-HLESource | 10.5% | 4.2% | DeepSeek V3.2 leads |
| AA-Omniscience IndexSource | -46.7% | -17.3% | Llama 3.1 405B leads |
| AA-Omniscience AccuracySource | 24.2% | 22.3% | DeepSeek V3.2 leads |
| AA-Omniscience Hallucination RateSource | 93.5% | 51.0% | Llama 3.1 405B leads |
Math2 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V3.2 | Llama 3.1 405B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1206 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V3.2 | Llama 3.1 405B | Result |
|---|---|---|---|
| AA-IFBenchSource | 49.0% | 39.0% | DeepSeek V3.2 leads |
Frequently Asked Questions (3)
Can I compare DeepSeek V3.2 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 V3.2 and Llama 3.1 405B today?
DeepSeek V3.2: $0.28 input / $0.42 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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