Ling-3.0-flash vs Qwen3.5 397B A17B
Wins 3 of 7 areas
Coding · Agents · Math
Wins 3 of 7 areas
Reasoning · Long documents · Following instructions
The two are evenly matched.Ling-3.0-flash is better at agents and coding; Qwen3.5 397B A17B at reasoning and long documents.
Scores updated · 26 tests both models report · How we compare
Where each one wins
Tests won in each of the seven 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.
- AgentsCarrying out multi-step tasks on its own30Ling-3.0-flash3 of 4 tests · 1 tie
- CodingWriting and fixing software31Ling-3.0-flash3 of 5 tests · 1 tie
- MathCompetition and research-level math20Ling-3.0-flash2 of 3 tests · 1 tie
- ReasoningHard problems that need careful thinking02Qwen3.5 397B A17B2 of 3 tests · 1 tie
- Long documentsFinding answers in very long texts01Qwen3.5 397B A17B1 of 1 test
- Following instructionsDoing exactly what it is asked01Qwen3.5 397B A17B1 of 1 test
- FactsGetting facts right instead of making them up11Even1 each
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.
Ling-3.0-flash costs 93% less for the same work.
The biggest differences
The three tests each model wins by the widest margin. Scores are out of 100.
Where Ling-3.0-flash pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+44.8points ahead
- Customer-service tasks in a simulated bankτ-Bench V3 · Banking+13.8points ahead
- Real work tasks from 44 professionsGDPVal+7.6points ahead
Where Qwen3.5 397B A17B pulls ahead
- Answers hard knowledge questions correctlyAA-Omniscience · Accuracy+12.6points ahead
- Very hard expert questions across many subjectsHumanity's Last Exam+5.3points ahead
- Reasons across sets of long documentsAA-LCR+4.3points ahead
Every test, side by side
All 26 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingLing-3.0-flash
- SWE-bench ProLing-3.0-flash by 5.756.650.9+5.7
- Terminal-Bench 2.1Ling-3.0-flash by 4.155.451.3+4.1
- SWE-bench MultilingualLing-3.0-flash by 3.172.469.3+3.1
- SciCodeQwen3.5 397B A17B by 2.84244.8+2.8
- LiveCodeBench v6tie82.883.6tie
AgentsLing-3.0-flash
- τ-Bench V3 · BankingLing-3.0-flash by 13.827.213.4+13.8
- GDPValLing-3.0-flash by 7.622.414.8+7.6
- BrowseCompLing-3.0-flash by 3.272.269+3.2
- Terminal-Bench 4.0tie00tie
ReasoningQwen3.5 397B A17B
- Humanity's Last ExamQwen3.5 397B A17B by 5.323.729+5.3
- GPQA DiamondQwen3.5 397B A17B by 3.885.589.3+3.8
- CritPttie1.71.7tie
FactsEven
- AA-Omniscience · Non-hallucinationLing-3.0-flash by 44.855.911.1+44.8
- AA-Omniscience · AccuracyQwen3.5 397B A17B by 12.618.230.8+12.6
MathLing-3.0-flash
- IMOAnswerBenchLing-3.0-flash by 2.883.780.9+2.8
- AIME 2026Ling-3.0-flash by 1.993.291.3+1.9
- HMMT Feb. 2026tie8787.9tie
Following instructionsQwen3.5 397B A17B
- IFBenchQwen3.5 397B A17B by 4.374.578.8+4.3
Other results7 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.
- τ³-Bench BankingLing-3.0-flash by 14.62813.4+14.6
- AA-OmniscienceLing-3.0-flash by 12.8-17.9-30.8+12.8
- AA Agentic IndexLing-3.0-flash by 10.42110.6+10.4
- Artificial Analysis Coding IndexLing-3.0-flash by 2.450.648.2+2.4
- AA IntelligenceLing-3.0-flash by 1.720.118.4+1.7
- WideSearchtie73.674tie
- BFCLv4tie7372.9tie
Questions people ask
Which is better, Ling-3.0-flash or Qwen3.5 397B A17B?
Ling-3.0-flash and Qwen3.5 397B A17B each win three of the seven areas where both have results. Ling-3.0-flash wins coding, agents and math; Qwen3.5 397B A17B wins reasoning, long documents and following instructions. Ling-3.0-flash costs 93% less. They are level on facts.
Which is better for coding?
Ling-3.0-flash. It wins 3 of the 5 coding tests both models report; Qwen3.5 397B A17B wins 1, and 1 is a tie.
Which is cheaper?
Ling-3.0-flash costs $0.07 per million input tokens and $0.22 per million output tokens; Qwen3.5 397B A17B costs $0.60 and $3.60. That makes Ling-3.0-flash about 93% cheaper for the same work.
How do you compare the two?
We use the 26 benchmark tests both models have published scores on. The verdict counts the 19 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 7 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.