Ling-3.0-flash vs Qwen3.7 Max
Wins 0 of 7 areas
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Wins 7 of 7 areas
Coding · Agents · Reasoning · Facts · Math · Long documents · Following instructions
Qwen3.7 Max is the stronger all-rounder.Ling-3.0-flash is cheaper.
Scores updated · 25 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.
- CodingWriting and fixing software05Qwen3.7 Max5 of 5 tests
- ReasoningHard problems that need careful thinking03Qwen3.7 Max3 of 3 tests
- MathCompetition and research-level math03Qwen3.7 Max3 of 3 tests
- AgentsCarrying out multi-step tasks on its own13Qwen3.7 Max3 of 4 tests
- FactsGetting facts right instead of making them up02Qwen3.7 Max2 of 2 tests
- Long documentsFinding answers in very long texts01Qwen3.7 Max1 of 1 test
- Following instructionsDoing exactly what it is asked01Qwen3.7 Max1 of 1 test
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 97% 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 Qwen3.7 Max pulls ahead
- Command-line tasks in a real terminalTerminal-Bench 2.1+19.1points ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+18.5points ahead
- Very hard expert questions across many subjectsHumanity's Last Exam+16.8points ahead
Where Ling-3.0-flash pulls ahead
- Customer-service tasks in a simulated bankτ-Bench V3 · Banking+15.4points ahead
Every test, side by side
All 25 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingQwen3.7 Max
- Terminal-Bench 2.1Qwen3.7 Max by 19.155.474.5+19.1
- LiveCodeBench v6Qwen3.7 Max by 8.882.891.6+8.8
- SciCodeQwen3.7 Max by 7.54249.5+7.5
- SWE-bench MultilingualQwen3.7 Max by 5.972.478.3+5.9
- SWE-bench ProQwen3.7 Max by 456.660.6+4
AgentsQwen3.7 Max
- τ-Bench V3 · BankingLing-3.0-flash by 15.427.211.8+15.4
- MCP AtlasQwen3.7 Max by 10.965.576.4+10.9
- GDPValQwen3.7 Max by 9.222.431.6+9.2
- Terminal-Bench 4.0Qwen3.7 Max by 1.501.5+1.5
ReasoningQwen3.7 Max
- Humanity's Last ExamQwen3.7 Max by 16.823.740.5+16.8
- CritPtQwen3.7 Max by 11.71.713.4+11.7
- GPQA DiamondQwen3.7 Max by 6.885.592.3+6.8
FactsQwen3.7 Max
- AA-Omniscience · Non-hallucinationQwen3.7 Max by 18.555.974.4+18.5
- AA-Omniscience · AccuracyQwen3.7 Max by 12.918.231.1+12.9
MathQwen3.7 Max
- HMMT Feb. 2026Qwen3.7 Max by 10.18797.1+10.1
- IMOAnswerBenchQwen3.7 Max by 6.383.790+6.3
- AIME 2026Qwen3.7 Max by 3.893.297+3.8
Following instructionsQwen3.7 Max
- IFBenchQwen3.7 Max by 674.580.5+6
Other results6 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-OmniscienceQwen3.7 Max by 31.4-17.913.5+31.4
- Artificial Analysis Coding IndexQwen3.7 Max by 15.450.666+15.4
- AA IntelligenceQwen3.7 Max by 9.420.129.5+9.4
- AA Agentic IndexQwen3.7 Max by 2.92123.9+2.9
- BFCLv4Qwen3.7 Max by 27375+2
- WideSearchQwen3.7 Max by 1.673.675.2+1.6
Questions people ask
Which is better, Ling-3.0-flash or Qwen3.7 Max?
Qwen3.7 Max wins all seven areas where both have results: coding, agents, reasoning, facts, math, long documents and following instructions. Ling-3.0-flash wins none, but costs 97% less.
Which is better for coding?
Qwen3.7 Max. It wins 5 of the 5 coding tests both models report; Ling-3.0-flash wins none.
Which is cheaper?
Ling-3.0-flash costs $0.07 per million input tokens and $0.22 per million output tokens; Qwen3.7 Max costs $2.50 and $7.50. That makes Ling-3.0-flash about 97% cheaper for the same work.
How do you compare the two?
We use the 25 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 6 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.