Command A vs Jamba 1.7 Large
Wins 3 of 6 areas
Reasoning · Long documents · Following instructions
Wins 0 of 6 areas
—
Command A wins more areas, narrowly.
Scores updated · 19 tests both models report · How we compare
Where each one wins
Tests won in each of the six 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 thinking10Command A1 of 3 tests · 2 ties
- Long documentsFinding answers in very long texts10Command A1 of 1 test
- Following instructionsDoing exactly what it is asked10Command A1 of 1 test
- CodingWriting and fixing software11Even1 each
- AgentsCarrying out multi-step tasks on its own00Even0 each · 1 tie
- FactsGetting facts right instead of making them up11Even1 each · 1 tie
Agents, long documents and following instructions 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 Command A pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+17.8points ahead
- Graduate-level biology, physics and chemistry questionsGPQA Diamond+13.7points ahead
- Code for real scientific research problemsSciCode+9.3points ahead
Where Jamba 1.7 Large pulls ahead
- Answers hard knowledge questions correctlyAA-Omniscience · Accuracy+4.2points ahead
- Hard command-line tasks in a real terminalTerminal-Bench Hard+1.5points ahead
Every test, side by side
All 19 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingEven
- SciCodeCommand A by 9.328.118.8+9.3
- Terminal-Bench HardJamba 1.7 Large by 1.50.82.3+1.5
ReasoningCommand A
- GPQA DiamondCommand A by 13.752.739+13.7
- Humanity's Last Examtie43.7tie
- CritPttie00tie
FactsEven
- AA-Omniscience · Non-hallucinationCommand A by 17.822.74.9+17.8
- AA-Omniscience · AccuracyJamba 1.7 Large by 4.216.420.6+4.2
- Vectara HHEM hallucination ratelower is bettertie9.39.7tie
Following instructionsCommand A
- IFBenchCommand A by 1.336.535.2+1.3
Other results8 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-OmniscienceCommand A by 6.6-48.3-54.9+6.6
- vectara_avg_summary_lengthJamba 1.7 Large by 23.1 rating points101.7124.8+23.1 rating
- Artificial Analysis Coding IndexCommand A by 2.19.97.8+2.1
- τ²-Bench Telecom (AA run)Command A by 1.715.213.5+1.7
- vectara_answer_rateJamba 1.7 Large by 1.397.698.9+1.3
- AA Intelligencetie76.1tie
- AA Agentic Indextie5.14.5tie
- vectara_factual_consistencytie90.790.3tie
Questions people ask
Which is better, Command A or Jamba 1.7 Large?
Command A wins three of the six areas where both have results: reasoning, long documents and following instructions. Jamba 1.7 Large wins none. They are level on coding, agents and facts.
Which is better for coding?
Neither. They win 1 coding test each of the 2 both models report.
How do you compare the two?
We use the 19 benchmark tests both models have published scores on. The verdict counts the 11 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 8 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.