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Model comparison

Kimi K2.7 Code vs Mistral Large 2

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.

Moonshot AI
54.03/100
Margin
13.1pts
← winning
40.88/100
0 category wins0 category wins

Public leaderboard positions: Kimi K2.7 Code #92 (Estimated); Mistral Large 2 #172 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Kimi K2.7 Code and Mistral Large 2 share 11 comparable benchmark results. 0 of 8 categories are comparable. 12 results are unique to Kimi K2.7 Code; 0 to Mistral Large 2.

Updated July 27, 2026
Shared results
11
Kimi K2.7 Code only
12
Mistral Large 2 only
0
Comparable categories
0 / 8

Benchmark data for Kimi K2.7 Code and Mistral Large 2 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.

Kimi K2.7 Code has the larger context window at 256K, compared with 128K for Mistral Large 2.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Operational comparison

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

MetricKimi K2.7 CodeMistral Large 2Comparison
Input / output priceUSD per 1M tokensKimi K2.7 Code$0.95 input / $4 outputMistral Large 2Not availableA complete price comparison is not available.
Generation speedtokens per secondKimi K2.7 CodeNot availableMistral Large 238 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenKimi K2.7 CodeNot availableMistral Large 21.45 sA complete latency comparison is not available.
Context windowmaximum listed tokensKimi K2.7 Code256KMistral Large 2128KKimi K2.7 Code lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkKimi K2.7 CodeMistral Large 2Result
Kimi Claw 24/7Source 46.9%Not comparable
MCP AtlasSource 76%Not comparable
MCP Mark VerifiedSource 81.1%Not comparable
AA Agentic IndexSource 29.6%Not comparable
τ²-bench resultsSource 90.1%30.7%Kimi K2.7 Code leads
GDPval-AASource 34.3%Not comparable
GDPval-AASource 1186Not comparable
Coding
BenchmarkKimi K2.7 CodeMistral Large 2Result
Kimi Code Bench v2Source 62.0%Not comparable
ProgramBenchSource 53.6%Not comparable
MLS-Bench LiteSource 35.1%Not comparable
cursorBench32Source 49.7%Not comparable
AA Coding IndexSource 60.8%Not comparable
AA-SciCodeSource 47.5%29.2%Kimi K2.7 Code leads
Reasoning
BenchmarkKimi K2.7 CodeMistral Large 2Result
AA-LCRSource 66.3%5.3%Kimi K2.7 Code leads
CritPtSource 10.0%0.0%Kimi K2.7 Code leads
Knowledge
BenchmarkKimi K2.7 CodeMistral Large 2Result
Artificial Analysis Intelligence IndexSource 42.0%9.2%Kimi K2.7 Code leads
AA-GPQA DiamondSource 89.6%48.6%Kimi K2.7 Code leads
AA-HLESource 32.8%4.0%Kimi K2.7 Code leads
AA-Omniscience IndexSource -10.7%-34.0%Kimi K2.7 Code leads
AA-Omniscience AccuracySource 38.6%20.1%Kimi K2.7 Code leads
AA-Omniscience Hallucination RateSource 80.3%67.8%Mistral Large 2 leads
Multimodal
BenchmarkKimi K2.7 CodeMistral Large 2Result
Design Arena WebsiteSource 1300Not comparable
Inst. Following
BenchmarkKimi K2.7 CodeMistral Large 2Result
AA-IFBenchSource 63.1%31.2%Kimi K2.7 Code leads
Frequently Asked Questions (3)

Can I compare Kimi K2.7 Code and Mistral Large 2 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 Kimi K2.7 Code and Mistral Large 2 today?

Kimi K2.7 Code: $0.95 input / $4.00 output per 1M tokens Mistral Large 2: Pricing unavailable 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.

Kimi K2.7 Code
API / mo$3,713
Self-host / mo$18,221
Break-even326M/day
Mistral Large 2
API / mo$0
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Model the full break-even

Related Comparisons

Last updated: July 27, 2026

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