Standard Compute
Model comparison 2026

GPT-6 Astra vs Muse Wonder

GPT-6 Astra
OpenAI · Frontier · Proprietary
$22/1M · 1.1M ctx
Muse Wonder
Meta · Frontier · Proprietary
$8.80/1M · 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
GPT-6 Astra
Muse Wonder
Maker
OpenAI
Meta
Blended price / 1M
$22
$8.80
Input / output
$10 in · $50 out / 1M tokens
$4.00 in · $20 out / 1M tokens
Context window
1.1M
1.0M
Open weights
No
No
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
9.3
9.3
Agentic Ability
9.5
9.0
Speed
6.7
8.0
Value for money
4.0
5.4
Reliability
9.3
9.0

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

Verdict: GPT-6 Astra or Muse Wonder?

Updated 2026-10-13

Choose GPT-6 Astra if you want the hardest coding and research tasks in OpenAI-based stacks, where cost is secondary. Choose Muse Wonder if you want multimodal agent work where you want a frontier model outside the usual three vendors.

Editorially it's close: each model leads in 2 of our five dimensions. On price, GPT-6 Astra runs about $22 per 1M tokens (blended) and is proprietary; Muse Wonder is about $8.80 and proprietary.

Where GPT-6 Astra falls short
  • About six times GPT-6.1 Sol's cost per request for the same tbench.ai Terminal-Bench 4.0 score
  • About 62 output tokens/s at max effort, per Artificial Analysis
Full GPT-6 Astra breakdown →
Where Muse Wonder falls short
  • Same price as Claude Opus 5.5 ($4/$20) but lower on Artificial Analysis and Terminal-Bench 4.0
  • Closed weights, unlike Meta's Llama models
Full Muse Wonder breakdown →

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