Standard Compute
Model comparison 2026

Kimi K2.7 Code vs Muse Spark Open

Kimi K2.7 Code
Moonshot AI · Balanced · Open weights
$1.48/1M · 262K ctx
Muse Spark Open
Meta · Balanced · Open weights
$2.15/1M · 1.0M 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
Kimi K2.7 Code
Muse Spark Open
Maker
Moonshot AI
Meta
Blended price / 1M
$1.48
$2.15
Input / output
$0.67 in · $3.35 out / 1M tokens
$1.25 in · $4.25 out / 1M tokens
Context window
262K
1.0M
Open weights
Yes
Yes
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
5.8
7.0
Agentic Ability
4.7
5.0
Speed
7.1
7.0
Value for Money
5.5
5.3
Reliability
8.4
8.0

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

Verdict: Kimi K2.7 Code or Muse Spark Open?

Updated 2026-10-16

Choose Kimi K2.7 Code if you want coding agents that need an open-weight model with a coding-specific tune. Choose Muse Spark Open if you want trying Meta's open-weight coding model through OpenRouter, or self-hosting it where code must stay on your own hardware.

In our editorial scoring, Kimi K2.7 Code leads in 3 of five dimensions (speed, value for money and reliability), while Muse Spark Open leads in 2. On price, Kimi K2.7 Code runs about $1.48 per 1M tokens (blended) and is open-weight; Muse Spark Open is about $2.15 and open-weight.

Where Kimi K2.7 Code falls short
  • Weak on long agentic tasks (1.0% in Artificial Analysis's Terminal-Bench 4.0 run)
  • 262K context, smaller than 11.7% of the coding-agent requests we measured
Full Kimi K2.7 Code breakdown →
Where Muse Spark Open falls short
  • No independent agent benchmark results yet; the published figures are Meta's own
  • Self-hosting needs at least 700 GB of GPU memory in NVFP4 (2 TB in BF16), per Meta's model card
Full Muse Spark Open breakdown →

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