Muse Ember is the stronger all-rounder.
Scores updated · 6 tests both models report · How we compare
Where each one wins
Tests won in each of the two areas where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
Coding and agents rest on a single test each.
What it costs
Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.
The biggest differences
The tests each model wins by the widest margin, up to three each. Scores are out of 100.
Where Muse Ember pulls ahead
- Complex command-line tasks across many fieldsTerminal-Bench 4.0+8.1points ahead
Where Claude Haiku 5.5 pulls ahead
No clear win on a test scored out of 100.
Every test, side by side
All 6 tests both models report. The winning score is in its model's colour; marks a score checked independently.
Other results4 tests, not counted
Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.
- CritPt v2 HardClaude Haiku 5.5 by 4.543.539+4.5
- HLE-DiamondClaude Haiku 5.5 by 4.529.625.1+4.5
- GDP (Surge AI)Muse Ember by 220.822.8+2
- Terminal-Bench-Science 0.1tie2020tie
Questions people ask
Which is better, Claude Haiku 5.5 or Muse Ember?
Muse Ember wins all two areas where both have results: coding and agents. Claude Haiku 5.5 wins none.
Which is better for coding?
Muse Ember. It wins the one coding test both models report.
Which is cheaper?
Claude Haiku 5.5 costs $0.10 per million input tokens and $0.50 per million output tokens; Muse Ember costs $0.10 and $0.50. For a million tokens read plus a million written, they cost about the same.
How do you compare the two?
We use the 6 benchmark tests both models have published scores on. The verdict counts the 2 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 4 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.