DeepSeek-V3.2-Exp vs GLM-4.6
Wins 5 of 6 areas
Coding · Reasoning · Facts · Long documents · Following instructions
Wins 0 of 6 areas
—
DeepSeek-V3.2-Exp is the stronger all-rounder.
Scores updated · 31 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.
- FactsGetting facts right instead of making them up20DeepSeek-V3.2-Exp2 of 3 tests · 1 tie
- CodingWriting and fixing software21DeepSeek-V3.2-Exp2 of 5 tests · 2 ties
- ReasoningHard problems that need careful thinking10DeepSeek-V3.2-Exp1 of 3 tests · 2 ties
- Long documentsFinding answers in very long texts10DeepSeek-V3.2-Exp1 of 1 test
- Following instructionsDoing exactly what it is asked10DeepSeek-V3.2-Exp1 of 1 test
- AgentsCarrying out multi-step tasks on its own11Even1 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.
DeepSeek-V3.2-Exp costs 75% 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 DeepSeek-V3.2-Exp pulls ahead
- Reasons across sets of long documentsAA-LCR+18.3points ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+13.3points ahead
- Real work tasks from 44 professionsGDPVal+12points ahead
Where GLM-4.6 pulls ahead
- Finds hard-to-locate facts by browsing the webBrowseComp+5points ahead
Every test, side by side
All 31 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingDeepSeek-V3.2-Exp
- LMArena · WebDevGLM-4.6 by 69 rating points12721341+69 rating
- Terminal-Bench HardDeepSeek-V3.2-Exp by 6.131.125+6.1
- SWE-bench MultilingualDeepSeek-V3.2-Exp by 4.157.953.8+4.1
- SciCodetie37.738.4tie
- SWE-bench Verifiedtie67.868tie
ReasoningDeepSeek-V3.2-Exp
- GPQA DiamondDeepSeek-V3.2-Exp by 1.779.778+1.7
- Humanity's Last Examtie14.914.5tie
- CritPttie1.41.1tie
FactsDeepSeek-V3.2-Exp
- AA-Omniscience · Non-hallucinationDeepSeek-V3.2-Exp by 13.319.25.9+13.3
- Vectara HHEM hallucination ratelower is betterDeepSeek-V3.2-Exp by 4.25.39.5+4.2
- AA-Omniscience · Accuracytie27.626.9tie
Long documentsDeepSeek-V3.2-Exp
- AA-LCRDeepSeek-V3.2-Exp by 18.372.354+18.3
Following instructionsDeepSeek-V3.2-Exp
- IFBenchDeepSeek-V3.2-Exp by 10.754.143.4+10.7
Other results16 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)GLM-4.6 by 36.633.970.5+36.6
- vectara_avg_summary_lengthGLM-4.6 by 12.664.677.2+12.6
- Artificial Analysis Coding IndexGLM-4.6 by 12.533.345.8+12.5
- AA-OmniscienceDeepSeek-V3.2-Exp by 10.9-31-41.9+10.9
- AA Agentic IndexDeepSeek-V3.2-Exp by 10.128.718.6+10.1
- HMMT Nov. 2025GLM-4.6 by 7.584.291.7+7.5
- LiveCodeBenchGLM-4.6 by 5.474.179.5+5.4
- HMMT 2025GLM-4.6 by 5.183.688.7+5.1
- AIME 2025GLM-4.6 by 4.689.393.9+4.6
- vectara_factual_consistencyDeepSeek-V3.2-Exp by 4.294.790.5+4.2
- Terminal-BenchGLM-4.6 by 2.837.740.5+2.8
- vectara_answer_rateDeepSeek-V3.2-Exp by 2.196.694.5+2.1
- AA IntelligenceGLM-4.6 by 1.916.618.5+1.9
- MMLU-ProDeepSeek-V3.2-Exp by 1.88583.2+1.8
- BrowseComp-ZHGLM-4.6 by 1.647.949.5+1.6
- HMMT Feb. 2025tie9089.2tie
Questions people ask
Which is better, DeepSeek-V3.2-Exp or GLM-4.6?
DeepSeek-V3.2-Exp wins five of the six areas where both have results: coding, reasoning, facts, long documents and following instructions. GLM-4.6 wins none. They are level on agents.
Which is better for coding?
DeepSeek-V3.2-Exp. It wins 2 of the 5 coding tests both models report; GLM-4.6 wins 1, and 2 are ties.
Which is cheaper?
DeepSeek-V3.2-Exp costs $0.28 per million input tokens and $0.42 per million output tokens; GLM-4.6 costs $0.57 and $2.20. That makes DeepSeek-V3.2-Exp about 75% cheaper for the same work.
How do you compare the two?
We use the 31 benchmark tests both models have published scores on. The verdict counts the 15 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 16 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.