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Model comparison

Llama 3.1 405B vs Mixtral 8x22B Instruct v0.1

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

No sourced benchmark result is currently shared by both models. This page therefore compares only the available metadata, pricing, and runtime rows; it does not name a quality winner.
50.94/100
No comparison
0 category wins0 category wins

Public leaderboard positions: Llama 3.1 405B #107 (Estimated); Mixtral 8x22B Instruct v0.1 #131 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Llama 3.1 405B and Mixtral 8x22B Instruct v0.1 share 0 comparable benchmark results. 0 of 8 categories are comparable. 11 results are unique to Llama 3.1 405B; 0 to Mixtral 8x22B Instruct v0.1.

Updated July 24, 2026
Shared results
0
Llama 3.1 405B only
11
Mixtral 8x22B Instruct v0.1 only
0
Comparable categories
0 / 8

Benchmark data for Llama 3.1 405B and Mixtral 8x22B Instruct v0.1 is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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 does not have sourced benchmark coverage for Mixtral 8x22B Instruct v0.1 yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.

Llama 3.1 405B has the larger context window at 128K, compared with 64K for Mixtral 8x22B Instruct v0.1.

Operational comparison

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

MetricLlama 3.1 405BMixtral 8x22B Instruct v0.1Comparison
Input / output priceUSD per 1M tokensLlama 3.1 405B$0 input / $0 outputMixtral 8x22B Instruct v0.1$0 input / $0 outputListed prices are equal.
Generation speedtokens per secondLlama 3.1 405B29 tok/sMixtral 8x22B Instruct v0.1Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenLlama 3.1 405B2.19 sMixtral 8x22B Instruct v0.1Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensLlama 3.1 405B128KMixtral 8x22B Instruct v0.164KLlama 3.1 405B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkLlama 3.1 405BMixtral 8x22B Instruct v0.1Result
τ²-bench resultsSource 19%Not comparable
Coding
BenchmarkLlama 3.1 405BMixtral 8x22B Instruct v0.1Result
AA-SciCodeSource 29.9%Not comparable
Reasoning
BenchmarkLlama 3.1 405BMixtral 8x22B Instruct v0.1Result
AA-LCRSource 24.3%Not comparable
CritPtSource 0.0%Not comparable
Knowledge
BenchmarkLlama 3.1 405BMixtral 8x22B Instruct v0.1Result
Artificial Analysis Intelligence IndexSource 8.5%Not comparable
AA-GPQA DiamondSource 51.5%Not comparable
AA-HLESource 4.2%Not comparable
AA-Omniscience IndexSource -17.3%Not comparable
AA-Omniscience AccuracySource 22.3%Not comparable
AA-Omniscience Hallucination RateSource 51.0%Not comparable
Inst. Following
BenchmarkLlama 3.1 405BMixtral 8x22B Instruct v0.1Result
AA-IFBenchSource 39.0%Not comparable
Frequently Asked Questions (3)

Can I compare Llama 3.1 405B and Mixtral 8x22B Instruct v0.1 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 Llama 3.1 405B and Mixtral 8x22B Instruct v0.1 today?

Llama 3.1 405B: $0.00 input / $0.00 output per 1M tokens Mixtral 8x22B Instruct v0.1: $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 24, 2026