o4-mini vs Qwen3.6 27B
Wins 3 of 8 areas
Agents · Math · Following instructions
Wins 4 of 8 areas
Coding · Reasoning · Images and charts · Long documents
Qwen3.6 27B wins more areas, narrowly.o4-mini is better at agents.
Scores updated · 21 tests both models report · How we compare
Where each one wins
Tests won in each of the eight areas we test. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
- Images and chartsUnderstanding pictures, charts and video04Qwen3.6 27B4 of 4 tests
- ReasoningHard problems that need careful thinking02Qwen3.6 27B2 of 3 tests · 1 tie
- CodingWriting and fixing software12Qwen3.6 27B2 of 3 tests
- Long documentsFinding answers in very long texts01Qwen3.6 27B1 of 1 test
- AgentsCarrying out multi-step tasks on its own10o4-mini1 of 1 test
- MathCompetition and research-level math10o4-mini1 of 1 test
- Following instructionsDoing exactly what it is asked10o4-mini1 of 1 test
- FactsGetting facts right instead of making them up11Even1 each
Agents, math, 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.
Qwen3.6 27B costs 24% less for the same work.
The biggest differences
The three tests each model wins by the widest margin. Scores are out of 100.
Where Qwen3.6 27B pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+31.2points ahead
- Hard command-line tasks in a real terminalTerminal-Bench Hard+19.6points ahead
- Reasons across sets of long documentsAA-LCR+16.3points ahead
Where o4-mini pulls ahead
- Answers hard knowledge questions correctlyAA-Omniscience · Accuracy+5.2points ahead
- Code for real scientific research problemsSciCode+3.7points ahead
- Follows unfamiliar, precisely checkable instructionsIFBench+1.1points ahead
Every test, side by side
All 21 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingQwen3.6 27B
- Terminal-Bench HardQwen3.6 27B by 19.615.234.8+19.6
- SWE-bench VerifiedQwen3.6 27B by 9.168.177.2+9.1
- SciCodeo4-mini by 3.746.542.8+3.7
ReasoningQwen3.6 27B
- Humanity's Last ExamQwen3.6 27B by 6.616.523.1+6.6
- GPQA DiamondQwen3.6 27B by 5.878.484.2+5.8
- CritPttie0.61.1tie
FactsEven
- AA-Omniscience · Non-hallucinationQwen3.6 27B by 31.219.550.7+31.2
- AA-Omniscience · Accuracyo4-mini by 5.224.819.6+5.2
Images and chartsQwen3.6 27B
- CharXiv (RQ)Qwen3.6 27B by 6.47278.4+6.4
- MMMU-ProQwen3.6 27B by 5.469.274.6+5.4
- MathVistaQwen3.6 27B by 3.184.387.4+3.1
- MMMUQwen3.6 27B by 1.381.682.9+1.3
Other results5 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.
- τ²-Bench Telecom (AA run)Qwen3.6 27B by 38.655.694.2+38.6
- Artificial Analysis Coding IndexQwen3.6 27B by 28.125.653.7+28.1
- AA Agentic Indexo4-mini by 1636.120.1+16
- AA-OmniscienceQwen3.6 27B by 15.7-35.7-20+15.7
- AA IntelligenceQwen3.6 27B by 4.716.721.4+4.7
Questions people ask
Which is better, o4-mini or Qwen3.6 27B?
Qwen3.6 27B wins four of the eight areas we test: coding, reasoning, images and charts and long documents. o4-mini wins agents, math and following instructions. They are level on facts.
Which is better for coding?
Qwen3.6 27B. It wins 2 of the 3 coding tests both models report; o4-mini wins 1.
Which is cheaper?
o4-mini costs $1.10 per million input tokens and $4.40 per million output tokens; Qwen3.6 27B costs $0.60 and $3.60. That makes Qwen3.6 27B about 24% cheaper for the same work.
How do you compare the two?
We use the 21 benchmark tests both models have published scores on. The verdict counts the 16 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 5 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.