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DeepSeek V3.1 vs Kimi K2 0905

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 DeepSeek V3.1 and Kimi K2 0905.

DeepSeek

DeepSeek V3.1

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

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Moonshot AI

Kimi K2 0905

Kimi K2 0905 is the September update of [Kimi K2 0711](moonshotai/kimi-k2). It is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32...

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Technical Specifications

SpecificationDeepSeek V3.1Kimi K2 0905
ProviderDeepSeekMoonshot AI
Context Window163,840 tokens262,144 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelself hostablemanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-08-212025-09-04

API Pricing Comparison

Input Price per Million Tokens

DeepSeek V3.1

$0.21

Kimi K2 0905

$0.60

Output Price per Million Tokens

DeepSeek V3.1

$0.79

Kimi K2 0905

$2.50

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.

DeepSeek V3.1 Quirks & Gotchas

No developer gotchas reported.

Kimi K2 0905 Quirks & Gotchas

No developer gotchas reported.