Standard Compute
Model comparison 2026

DeepSeek V4.1 Flash vs Kimi K2.7 Code

DeepSeek V4.1 Flash
DeepSeek · Budget · Open weights
$0.22/1M · 1.0M ctx
Kimi K2.7 Code
Moonshot AI · Balanced · Open weights
$1.48/1M · 262K ctx

Community vote

Pick a winner in each dimension. You can change your vote any time.

Output Quality
Correctness and depth of what it produces
Agentic Ability
Tool calls, instruction-following, and multi-step tasks
Speed
Tokens per second and time-to-first-token
Value for money
How much capability you get per dollar
Reliability
Consistent results: fewer refusals, loops and format breaks

Specs and pricing side by side

Spec
DeepSeek V4.1 Flash
Kimi K2.7 Code
Maker
DeepSeek
Moonshot AI
Blended price / 1M
$0.22
$1.48
Input / output
$0.04 in · $0.63 out / 1M tokens
$0.67 in · $3.35 out / 1M tokens
Context window
1.0M
262K
Open weights
Yes
Yes
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
8.8
8.6
Agentic Ability
8.8
9.2
Speed
9.4
7.8
Value for money
10.0
9.2
Reliability
8.8
8.9

Pricing and capabilities synced from the OpenRouter catalogue. Scores are editorial (0–10).

Verdict: DeepSeek V4.1 Flash or Kimi K2.7 Code?

Updated 2026-10-13

Choose DeepSeek V4.1 Flash if you want cheap, high-volume open-weight agent work. Choose Kimi K2.7 Code if you want cheap, capable open-weight coding agents.

In our editorial scoring, DeepSeek V4.1 Flash leads in 3 of five dimensions (output quality, speed and value for money), while Kimi K2.7 Code leads in 2. On price, DeepSeek V4.1 Flash runs about $0.22 per 1M tokens (blended) and is open-weight; Kimi K2.7 Code is about $1.48 and open-weight.

Where DeepSeek V4.1 Flash falls short
  • Well below the frontier on long agentic tasks
  • DeepSeek API prices differ between peak and off-peak hours
Full DeepSeek V4.1 Flash breakdown →
Where Kimi K2.7 Code falls short
  • Below the very top models on hard reasoning
  • Throughput varies by host
Full Kimi K2.7 Code breakdown →

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