GLM-5.3-Flash vs Qwen3.5 122B A10B
Wins 6 of 6 areas
Coding · Agents · Reasoning · Facts · Images and charts · Long documents
Wins 0 of 6 areas
—
GLM-5.3-Flash is the stronger all-rounder.
Scores updated · 28 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.
- CodingWriting and fixing software40GLM-5.3-Flash4 of 4 tests
- ReasoningHard problems that need careful thinking30GLM-5.3-Flash3 of 3 tests
- AgentsCarrying out multi-step tasks on its own31GLM-5.3-Flash3 of 4 tests
- FactsGetting facts right instead of making them up20GLM-5.3-Flash2 of 2 tests
- Images and chartsUnderstanding pictures, charts and video20GLM-5.3-Flash2 of 2 tests
- Long documentsFinding answers in very long texts10GLM-5.3-Flash1 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.
GLM-5.3-Flash costs 82% 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 GLM-5.3-Flash pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+59.5points ahead
- Real work tasks from 44 professionsGDPVal+41.5points ahead
- Command-line tasks in a real terminalTerminal-Bench 2.1+36.7points ahead
Where Qwen3.5 122B A10B pulls ahead
- Completes tasks by operating a computer desktopOSWorld-Verified+43.2points ahead
Every test, side by side
All 28 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingGLM-5.3-Flash
- Terminal-Bench 2.1GLM-5.3-Flash by 36.784.347.6+36.7
- LMArena · WebDevGLM-5.3-Flash by 245 rating points16051360+245 rating
- SciCodeGLM-5.3-Flash by 11.951.639.7+11.9
- LiveCodeBench v6GLM-5.3-Flash by 1.780.678.9+1.7
AgentsGLM-5.3-Flash
- OSWorld-VerifiedQwen3.5 122B A10B by 43.214.858+43.2
- GDPValGLM-5.3-Flash by 41.557.215.7+41.5
- Terminal-Bench 4.0GLM-5.3-Flash by 32.832.80+32.8
- τ-Bench V3 · BankingGLM-5.3-Flash by 31.947.215.3+31.9
ReasoningGLM-5.3-Flash
- CritPtGLM-5.3-Flash by 14.815.40.6+14.8
- Humanity's Last ExamGLM-5.3-Flash by 14.739.925.2+14.7
- GPQA DiamondGLM-5.3-Flash by 5.591.285.7+5.5
FactsGLM-5.3-Flash
- AA-Omniscience · Non-hallucinationGLM-5.3-Flash by 59.572.412.9+59.5
- AA-Omniscience · AccuracyGLM-5.3-Flash by 3.127.524.4+3.1
Images and chartsGLM-5.3-Flash
- CharXiv (RQ)GLM-5.3-Flash by 12.289.477.2+12.2
- LMArena · VisionGLM-5.3-Flash by 51 rating points12961245+51 rating
Other results12 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-OmniscienceGLM-5.3-Flash by 497.5-41.5+49
- AA Agentic IndexGLM-5.3-Flash by 41.651.29.6+41.6
- AA IntelligenceGLM-5.3-Flash by 26.241.815.6+26.2
- Artificial Analysis Coding IndexGLM-5.3-Flash by 25.871.545.7+25.8
- Video-MME v2Qwen3.5 122B A10B by 17.214.832+17.2
- BabyVisionGLM-5.3-Flash by 13.253.440.2+13.2
- HLE, text-onlyGLM-5.3-Flash by 12.336.524.2+12.3
- OCRBench v2, ZHQwen3.5 122B A10B by 10.556.867.3+10.5
- SciCode, subtaskGLM-5.3-Flash by 10.35039.8+10.3
- MMVUGLM-5.3-Flash by 5.880.574.7+5.8
- MV-BenchGLM-5.3-Flash by 1.277.876.6+1.2
- MMLU-ProXtie8382.2tie
Questions people ask
Which is better, GLM-5.3-Flash or Qwen3.5 122B A10B?
GLM-5.3-Flash wins all six areas where both have results: coding, agents, reasoning, facts, images and charts and long documents. Qwen3.5 122B A10B wins none.
Which is better for coding?
GLM-5.3-Flash. It wins 4 of the 4 coding tests both models report; Qwen3.5 122B A10B wins none.
Which is cheaper?
GLM-5.3-Flash costs $0.15 per million input tokens and $0.50 per million output tokens; Qwen3.5 122B A10B costs $0.40 and $3.20. That makes GLM-5.3-Flash about 82% cheaper for the same work.
How do you compare the two?
We use the 28 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 12 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.