Standard Compute
Model comparison 2026

Llama 4 Maverick vs Muse Spark Open

Llama 4 Maverick
Meta · Budget · Open weights
$0.33/1M · 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
Llama 4 Maverick
Muse Spark Open
Maker
Meta
Meta
Blended price / 1M
$0.33
$2.15
Input / output
$0.19 in · $0.65 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
No
Yes
Output Quality
3.5
7.0
Agentic Ability
4.4
5.0
Speed
5.9
7.0
Value for Money
5.8
5.3
Reliability
8.4
8.0

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

Verdict: Llama 4 Maverick or Muse Spark Open?

Updated 2026-10-16

Choose Llama 4 Maverick if you want self-hosted setups built on the Llama ecosystem. 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, Muse Spark Open leads in 3 of five dimensions (output quality, agentic ability and speed), while Llama 4 Maverick leads in 2. On price, Llama 4 Maverick runs about $0.33 per 1M tokens (blended) and is open-weight; Muse Spark Open is about $2.15 and open-weight.

Where Llama 4 Maverick falls short
  • Not suited to agentic coding (0% in Artificial Analysis's Terminal-Bench 4.0 run)
  • About 44 output tokens/s, per Artificial Analysis
Full Llama 4 Maverick 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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