Standard Compute
Model comparison 2026

Mistral Large 4 vs Muse Spark Open

Mistral Large 4
Mistral · Balanced · Open weights
$1.10/1M · 1.0M 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
Mistral Large 4
Muse Spark Open
Maker
Mistral
Meta
Blended price / 1M
$1.10
$2.15
Input / output
$0.68 in · $2.09 out / 1M tokens
$1.25 in · $4.25 out / 1M tokens
Context window
1.0M
1.0M
Open weights
Yes
Yes
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
7.6
7.0
Agentic Ability
7.1
5.0
Speed
7.0
7.0
Value for Money
5.9
5.3
Reliability
8.8
8.0

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

Verdict: Mistral Large 4 or Muse Spark Open?

Updated 2026-10-16

Choose Mistral Large 4 if you want open-weight, EU-provenance agent work that needs long context and image input. 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, Mistral Large 4 leads in 4 of five dimensions (output quality, agentic ability, value for money and reliability), while Muse Spark Open leads in 0. On price, Mistral Large 4 runs about $1.10 per 1M tokens (blended) and is open-weight; Muse Spark Open is about $2.15 and open-weight.

Where Mistral Large 4 falls short
  • Still a public preview, so behavior and price can change
  • 26.8% in Artificial Analysis's Terminal-Bench 4.0 run, well below the frontier models
Full Mistral Large 4 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 →

Setting it up? Mistral Large 4: model ID, providers and agent config

The agent matters as much as the model. Compare AI agents →

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