Gemini 4 Argon is the stronger all-rounder.Muse Ember is cheaper.
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.
Muse Ember costs 95% less for the same work.
The biggest differences
The tests each model wins by the widest margin, up to three each. Scores are out of 100.
Where Gemini 4 Argon pulls ahead
- Complex command-line tasks across many fieldsTerminal-Bench 4.0+16.2points ahead
Where Muse Ember 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.
CodingGemini 4 Argon
- LMArena · WebDevGemini 4 Argon by 75 rating points16831608+75 rating
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.
- Terminal-Bench-Science 0.1Gemini 4 Argon by 32.952.920+32.9
- HLE-DiamondGemini 4 Argon by 31.656.725.1+31.6
- CritPt v2 HardGemini 4 Argon by 13.552.539+13.5
- GDP (Surge AI)Muse Ember by 121.822.8+1
Questions people ask
Which is better, Gemini 4 Argon or Muse Ember?
Gemini 4 Argon wins all two areas where both have results: coding and agents. Muse Ember wins none, but costs 95% less.
Which is better for coding?
Gemini 4 Argon. It wins the one coding test both models report.
Which is cheaper?
Gemini 4 Argon costs $2.00 per million input tokens and $10.00 per million output tokens; Muse Ember costs $0.10 and $0.50. That makes Muse Ember about 95% cheaper for the same work.
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.