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Kimi K2.7 Code vs o1

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Kimi K2.7 Code and o1.

Moonshot AI

Kimi K2.7 Code

MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts...

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OpenAI

o1

The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...

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Technical Specifications

SpecificationKimi K2.7 Codeo1
ProviderMoonshot AIOpenAI
Context Window262,144 tokens200,000 tokens
Agent SuitabilityN/A88/100
Time to First Token (TTFT)N/A2500 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-06-122024-12-17

API Pricing Comparison

Input Price per Million Tokens

Kimi K2.7 Code

$0.74

o1

$15.00

Output Price per Million Tokens

Kimi K2.7 Code

$3.50

o1

$60.00

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
8500.0%vs9180.0%
Kimi K2.7 Code
o1
HumanEvalPython coding & logic synthesis
9320.0%vs9450.0%
Kimi K2.7 Code
o1
MATHComplex mathematical problem solving
7650.0%vs9480.0%
Kimi K2.7 Code
o1
GPQAGraduate-level expert reasoning
4600.0%vs7830.0%
Kimi K2.7 Code
o1
HellaSwagCommonsense reasoning and inference
8600.0%vs9200.0%
Kimi K2.7 Code
o1
MT-BenchMulti-turn conversation flow quality
900.0%vs940.0%
Kimi K2.7 Code
o1

Kimi K2.7 Code Quirks & Gotchas

No developer gotchas reported.

o1 Quirks & Gotchas

  • โ–ธReasoning model โ€” high latency by design, not for real-time use
  • โ–ธBest for complex math/code reasoning where accuracy > speed
  • โ–ธUse o3-mini when you need reasoning with lower latency