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Model comparison

DeepSeek V3.2 vs Llama 3.1 405B

Data verified

Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

55.4/100
Margin
3.7pts
← winning
51.71/100
0 category wins0 category wins

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 scores and score margins for DeepSeek V3.2 and Llama 3.1 405B
CategoryDeepSeek V3.2ΔLlama 3.1 405B
CodingDeepSeek V3.260.9MarginNo overlapLlama 3.1 405BNot measured
MathDeepSeek V3.217.1MarginNo overlapLlama 3.1 405BNot measured

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricDeepSeek V3.2Llama 3.1 405BComparison
Input / output priceUSD per 1M tokensDeepSeek V3.2$0.28 input / $0.42 outputLlama 3.1 405B$0 input / $0 outputLlama 3.1 405B has the lower combined listed price.
Generation speedtokens per secondDeepSeek V3.235 tok/sLlama 3.1 405B29 tok/sDeepSeek V3.2 has the higher measured throughput.
First-answer latencyseconds to first tokenDeepSeek V3.23.75 sLlama 3.1 405B2.19 sLlama 3.1 405B reaches the first token sooner.
Context windowmaximum listed tokensDeepSeek V3.2128KLlama 3.1 405B128KListed context windows are equal.

Benchmark Deep Dive

Agentic
BenchmarkDeepSeek V3.2Llama 3.1 405BResult
Claw-EvalSource 40.2%Not comparable
VITA-BenchSource 18.5%Not comparable
τ²-bench resultsSource 78.9%19%DeepSeek V3.2 leads
Gert LabsSource 29.57%Not comparable
Coding
BenchmarkDeepSeek V3.2Llama 3.1 405BResult
SWE-RebenchSource 60.9%Not comparable
React Native EvalsSource 71.5%Not comparable
AA-SciCodeSource 38.7%29.9%DeepSeek V3.2 leads
Reasoning
BenchmarkDeepSeek V3.2Llama 3.1 405BResult
AA-LCRSource 39.0%24.3%DeepSeek V3.2 leads
CritPtSource 0.9%0.0%DeepSeek V3.2 leads
Knowledge
BenchmarkDeepSeek V3.2Llama 3.1 405BResult
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
Math
BenchmarkDeepSeek V3.2Llama 3.1 405BResult
FrontierMath v2 (Tiers 1-3)Source 22.100%Not comparable
FrontierMath v2 (Tier 4)Source 2.100%Not comparable
Multimodal
BenchmarkDeepSeek V3.2Llama 3.1 405BResult
Design Arena WebsiteSource 1206Not comparable
Inst. Following
BenchmarkDeepSeek V3.2Llama 3.1 405BResult
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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Last updated: July 20, 2026

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