Compare · ModelsLive · 2 picked · head to head
GPT-5 vs Kimi K2 0711
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
GPT-5 wins on 10/12 benchmarks
GPT-5 wins 10 of 12 shared benchmarks. Leads in coding · knowledge · language.
Category leads
coding·GPT-5knowledge·GPT-5language·GPT-5math·Kimi K2 0711reasoning·Kimi K2 0711
Hype vs Reality
Attention vs performance
GPT-5
#100 by perf·#4 by attention
Kimi K2 0711
#72 by perf·#17 by attention
Best value
Kimi K2 0711
4.2x better value than GPT-5
GPT-5
9.4 pts/$
$5.63/M
Kimi K2 0711
39.1 pts/$
$1.43/M
Vendor risk
Who is behind the model
OpenAI
$840.0B·Tier 1
Moonshot AI
$18.0B·Tier 1
Head to head
12 benchmarks · 2 models
GPT-5Kimi K2 0711
Aider polyglot
GPT-5 leads by +28.9
Aider Polyglot · measures how well AI models can edit code across multiple programming languages using the Aider coding assistant framework.
GPT-5
88.0
Kimi K2 0711
59.1
Fiction.LiveBench
GPT-5 leads by +36.1
Fiction.LiveBench · a continuously updated benchmark using recently published fiction to test reading comprehension and reasoning, preventing data contamination.
GPT-5
97.2
Kimi K2 0711
61.1
GSO-Bench
GPT-5 leads by +2.0
GSO-Bench · evaluates AI models on real-world open-source software engineering tasks, testing the ability to understand and resolve actual GitHub issues.
GPT-5
6.9
Kimi K2 0711
4.9
HELM · GPQA
GPT-5 leads by +13.9
GPT-5
79.1
Kimi K2 0711
65.2
HELM · IFEval
GPT-5 leads by +2.5
GPT-5
87.5
Kimi K2 0711
85.0
HELM · MMLU-Pro
GPT-5 leads by +4.4
GPT-5
86.3
Kimi K2 0711
81.9
HELM · Omni-MATH
Kimi K2 0711 leads by +0.7
GPT-5
64.7
Kimi K2 0711
65.4
HELM · WildBench
Kimi K2 0711 leads by +0.5
GPT-5
85.7
Kimi K2 0711
86.2
Lech Mazur Writing
GPT-5 leads by +0.4
Lech Mazur Writing · evaluates creative writing ability, assessing prose quality, narrative coherence, and stylistic sophistication.
GPT-5
86.0
Kimi K2 0711
85.6
SimpleBench
GPT-5 leads by +36.5
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
GPT-5
48.0
Kimi K2 0711
11.6
Terminal Bench
GPT-5 leads by +21.8
Terminal-Bench 2.0 · evaluates AI agents on real terminal-based coding tasks · writing scripts, debugging, running tests, and managing projects entirely through command-line interaction. Tests both code quality and terminal fluency. Claude Opus 4.7 scores 69.4%, demonstrating significant agentic terminal competence.
GPT-5
49.6
Kimi K2 0711
27.8
WeirdML
GPT-5 leads by +21.3
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
GPT-5
60.7
Kimi K2 0711
39.4
Full benchmark table
| Benchmark | GPT-5 | Kimi K2 0711 |
|---|---|---|
Aider polyglot Aider Polyglot · measures how well AI models can edit code across multiple programming languages using the Aider coding assistant framework. | 88.0 | 59.1 |
Fiction.LiveBench Fiction.LiveBench · a continuously updated benchmark using recently published fiction to test reading comprehension and reasoning, preventing data contamination. | 97.2 | 61.1 |
GSO-Bench GSO-Bench · evaluates AI models on real-world open-source software engineering tasks, testing the ability to understand and resolve actual GitHub issues. | 6.9 | 4.9 |
HELM · GPQA | 79.1 | 65.2 |
HELM · IFEval | 87.5 | 85.0 |
HELM · MMLU-Pro | 86.3 | 81.9 |
HELM · Omni-MATH | 64.7 | 65.4 |
HELM · WildBench | 85.7 | 86.2 |
Lech Mazur Writing Lech Mazur Writing · evaluates creative writing ability, assessing prose quality, narrative coherence, and stylistic sophistication. | 86.0 | 85.6 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 48.0 | 11.6 |
Terminal Bench Terminal-Bench 2.0 · evaluates AI agents on real terminal-based coding tasks · writing scripts, debugging, running tests, and managing projects entirely through command-line interaction. Tests both code quality and terminal fluency. Claude Opus 4.7 scores 69.4%, demonstrating significant agentic terminal competence. | 49.6 | 27.8 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 60.7 | 39.4 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $1.25 | $10.00 | 400K tokens (~200 books) | $34.38 | |
| $0.57 | $2.30 | 131K tokens (~66 books) | $10.03 |