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Model comparison

GPT-5.1-Codex vs Kimi K2.5

Data verified

Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

52.72/100
Margin
6.9pts
winning →
Kimi K2.5
Moonshot AI
59.66/100
0 category wins0 category wins

Public leaderboard positions: GPT-5.1-Codex #99 (Estimated); Kimi K2.5 #54 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-5.1-Codex and Kimi K2.5 share 15 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to GPT-5.1-Codex; 48 to Kimi K2.5.

Updated July 23, 2026
Shared results
15
GPT-5.1-Codex only
1
Kimi K2.5 only
48
Comparable categories
0 / 8

Benchmark data for GPT-5.1-Codex and Kimi K2.5 is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 6 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.

GPT-5.1-Codex has the larger context window at 400K, compared with 256K for Kimi K2.5.

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 GPT-5.1-Codex and Kimi K2.5
CategoryGPT-5.1-CodexΔKimi K2.5
AgenticGPT-5.1-CodexNot measuredMarginNo overlapKimi K2.555.0
CodingGPT-5.1-CodexNot measuredMarginNo overlapKimi K2.559.4
ReasoningGPT-5.1-CodexNot measuredMarginNo overlapKimi K2.561.0
KnowledgeGPT-5.1-CodexNot measuredMarginNo overlapKimi K2.556.9
MathGPT-5.1-CodexNot measuredMarginNo overlapKimi K2.560.6
MultilingualGPT-5.1-CodexNot measuredMarginNo overlapKimi K2.582.3
MultimodalGPT-5.1-CodexNot measuredMarginNo overlapKimi K2.578.5
Inst. FollowingGPT-5.1-CodexNot measuredMarginNo overlapKimi K2.593.9

Operational comparison

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

MetricGPT-5.1-CodexKimi K2.5Comparison
Input / output priceUSD per 1M tokensGPT-5.1-CodexNot availableKimi K2.5$0.6 input / $3 outputA complete price comparison is not available.
Generation speedtokens per secondGPT-5.1-CodexNot availableKimi K2.545 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenGPT-5.1-CodexNot availableKimi K2.52.38 sA complete latency comparison is not available.
Context windowmaximum listed tokensGPT-5.1-Codex400KKimi K2.5256KGPT-5.1-Codex lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGPT-5.1-CodexKimi K2.5Result
τ²-bench resultsSource 83%95.9%Kimi K2.5 leads
Gert LabsSource 49.68%45.88%GPT-5.1-Codex leads
JobBenchSource 26.2%8.7%GPT-5.1-Codex leads
Terminal-Bench 2.0Source —50.8%Not comparable
BrowseCompSource —60.6%Not comparable
Claw-EvalSource —52.3%Not comparable
QwenClawBenchSource —54.3%Not comparable
τ³-bench resultsSource —65.7%Not comparable
DeepSearchQASource —77.1%Not comparable
DeepPlanningSource —14.4%Not comparable
ToolathlonSource —27.8%Not comparable
MCP AtlasSource —29.5%Not comparable
MCP-TasksSource —59.1%Not comparable
WideResearchSource —72.7%Not comparable
APEX-Agents-AASource —11.5%Not comparable
ResearchClawBenchSource —14.0%Not comparable
AA Agentic IndexSource —21.7%Not comparable
GDPval-AASource —25.4%Not comparable
GDPval-AASource —1009Not comparable
Coding
BenchmarkGPT-5.1-CodexKimi K2.5Result
Vibe Code BenchSource 13.12%—Not comparable
AA-SciCodeSource 40.2%49.0%Kimi K2.5 leads
SWE-bench VerifiedSource —76.8%Not comparable
SWE-bench Verified*Source —70.8%Not comparable
LiveCodeBench v6Source —85.0%Not comparable
SWE-bench ProSource —50.7%Not comparable
SWE MultilingualSource —73%Not comparable
SWE-RebenchSource —58.5%Not comparable
React Native EvalsSource —77.2%Not comparable
SciCodeSource —48.7%Not comparable
AA Coding IndexSource —46.8%Not comparable
Reasoning
BenchmarkGPT-5.1-CodexKimi K2.5Result
AA-LCRSource 67.3%65.3%GPT-5.1-Codex leads
CritPtSource 5.7%3.1%GPT-5.1-Codex leads
LongBench v2Source —61%Not comparable
Knowledge
BenchmarkGPT-5.1-CodexKimi K2.5Result
Artificial Analysis Intelligence IndexSource 34.7%35.4%Kimi K2.5 leads
AA-GPQA DiamondSource 86.0%87.9%Kimi K2.5 leads
AA-HLESource 23.4%29.4%Kimi K2.5 leads
AA-Omniscience IndexSource -6.0%-8.1%GPT-5.1-Codex leads
AA-Omniscience AccuracySource 39.2%34.3%GPT-5.1-Codex leads
AA-Omniscience Hallucination RateSource 74.4%64.6%Kimi K2.5 leads
GPQASource —87.6%Not comparable
GPQA-DSource —87.6%Not comparable
SuperGPQASource —69.2%Not comparable
MMLU-ProSource —87.1%Not comparable
MMLU-Pro (Arcee)Source —87.1%Not comparable
HLESource —30.1%Not comparable
Math
BenchmarkGPT-5.1-CodexKimi K2.5Result
AIME 2025Source —96.1%Not comparable
AIME26Source —95.8%Not comparable
AIME25 (Arcee)Source —96.3%Not comparable
HMMT Feb 2025Source —95.4%Not comparable
HMMT Nov 2025Source —91.1%Not comparable
HMMT Feb 2026Source —87.1%Not comparable
MMAnswerBenchSource —81.8%Not comparable
FrontierMath v2 (Tiers 1-3)Source —27.900%Not comparable
FrontierMath v2 (Tier 4)Source —4.200%Not comparable
Multilingual
BenchmarkGPT-5.1-CodexKimi K2.5Result
MMLU-ProXSource —82.3%Not comparable
NOVA-63Source —56.0%Not comparable
Multimodal
BenchmarkGPT-5.1-CodexKimi K2.5Result
AA-MMMU-ProSource 72.5%75.4%Kimi K2.5 leads
Design Arena WebsiteSource 11911279Kimi K2.5 leads
MMMU-ProSource —78.5%Not comparable
Video-MMESource —87.4%Not comparable
MMVUSource —80.4%Not comparable
VideoMMMUSource —86.6%Not comparable
Inst. Following
BenchmarkGPT-5.1-CodexKimi K2.5Result
AA-IFBenchSource 70.0%70.2%Kimi K2.5 leads
IFEvalSource —93.9%Not comparable
Frequently Asked Questions (3)

Can I compare GPT-5.1-Codex and Kimi K2.5 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 GPT-5.1-Codex and Kimi K2.5 today?

Kimi K2.5: $0.60 input / $3.00 output per 1M tokens 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.

GPT-5.1-Codex
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Kimi K2.5
API / mo$2,700
Self-host / mo$5,221
Break-even132M/day
Model the full break-even

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