Celeris-1 vs G9v3-39A5B
Wins 0 of 5 areas
—
Wins 5 of 5 areas
Coding · Agents · Reasoning · Facts · Long documents
G9v3-39A5B is the stronger all-rounder.
Scores updated · 13 tests both models report · How we compare
Where each one wins
Tests won in each of the five 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.
- ReasoningHard problems that need careful thinking02G9v3-39A5B2 of 3 tests · 1 tie
- CodingWriting and fixing software02G9v3-39A5B2 of 2 tests
- AgentsCarrying out multi-step tasks on its own02G9v3-39A5B2 of 2 tests
- FactsGetting facts right instead of making them up02G9v3-39A5B2 of 2 tests
- Long documentsFinding answers in very long texts01G9v3-39A5B1 of 1 test
Long documents rests on a single test.
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 G9v3-39A5B pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+79.8points ahead
- Reasons across sets of long documentsAA-LCR+27.3points ahead
- Command-line tasks in a real terminalTerminal-Bench 2.1+21.4points ahead
Where Celeris-1 pulls ahead
No clear win on a test scored out of 100.
Every test, side by side
All 13 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingG9v3-39A5B
- Terminal-Bench 2.1G9v3-39A5B by 21.411.232.6+21.4
- SciCodeG9v3-39A5B by 15.221.636.8+15.2
AgentsG9v3-39A5B
- GDPValG9v3-39A5B by 30.5030.5+30.5
- τ-Bench V3 · BankingG9v3-39A5B by 18.23.922.1+18.2
ReasoningG9v3-39A5B
- GPQA DiamondG9v3-39A5B by 17.463.180.5+17.4
- Humanity's Last ExamG9v3-39A5B by 10.76.817.5+10.7
- CritPttie00.3tie
FactsG9v3-39A5B
- AA-Omniscience · Non-hallucinationG9v3-39A5B by 79.87.287+79.8
- AA-Omniscience · AccuracyG9v3-39A5B by 3.91114.9+3.9
Other results3 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.
- AA-OmniscienceG9v3-39A5B by 75.4-71.63.8+75.4
- Artificial Analysis Coding IndexG9v3-39A5B by 18.714.433.1+18.7
- AA IntelligenceG9v3-39A5B by 15.56.321.8+15.5
Questions people ask
Which is better, Celeris-1 or G9v3-39A5B?
G9v3-39A5B wins all five areas where both have results: coding, agents, reasoning, facts and long documents. Celeris-1 wins none.
Which is better for coding?
G9v3-39A5B. It wins 2 of the 2 coding tests both models report; Celeris-1 wins none.
How do you compare the two?
We use the 13 benchmark tests both models have published scores on. The verdict counts the 10 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 3 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.