DeepSeek-V4-Flash vs GLM-5.2
Wins 3 of 7 areas
Agents · Long documents · Following instructions
Wins 2 of 7 areas
Coding · Math
DeepSeek-V4-Flash wins more areas, narrowly.GLM-5.2 is better at coding.
Scores updated · 55 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.
- Following instructionsDoing exactly what it is asked20DeepSeek-V4-Flash2 of 2 tests
- AgentsCarrying out multi-step tasks on its own32DeepSeek-V4-Flash3 of 5 tests
- Long documentsFinding answers in very long texts10DeepSeek-V4-Flash1 of 1 test
- CodingWriting and fixing software05GLM-5.25 of 7 tests · 2 ties
- MathCompetition and research-level math15GLM-5.25 of 6 tests
- ReasoningHard problems that need careful thinking33Even3 each
- FactsGetting facts right instead of making them up11Even1 each · 1 tie
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.
DeepSeek-V4-Flash costs 70% less for the same work.
The biggest differences
The three tests each model wins by the widest margin. Scores are out of 100.
Where DeepSeek-V4-Flash pulls ahead
- Abstract visual puzzles that people can solveARC-AGI-2+38.6points ahead
- Answers hard knowledge questions correctlyAA-Omniscience · Accuracy+16.1points ahead
- Complex command-line tasks across many fieldsTerminal-Bench 4.0+11.1points ahead
Where GLM-5.2 pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+65.4points ahead
- Hard command-line tasks in a real terminalTerminal-Bench Hard+15.2points ahead
- Common-sense trick questionsSimpleBench+12.5points ahead
Every test, side by side
All 55 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingGLM-5.2
- LMArena · WebDevGLM-5.2 by 175 rating points14301605+175 rating
- Terminal-Bench HardGLM-5.2 by 15.235.650.8+15.2
- SWE-bench ProGLM-5.2 by 9.552.662.1+9.5
- LiveBench · Agentic CodingGLM-5.2 by 546.851.8+5
- LiveBench · CodingGLM-5.2 by 4.77579.7+4.7
- SciCodetie50.351.2tie
- Terminal-Bench 2.1tie78.777.9tie
AgentsDeepSeek-V4-Flash
- AA IT-Bench SREGLM-5.2 by 11.231.542.7+11.2
- Terminal-Bench 4.0DeepSeek-V4-Flash by 11.112.11+11.1
- MCP AtlasGLM-5.2 by 7.86976.8+7.8
- τ-Bench V3 · BankingDeepSeek-V4-Flash by 4.839.434.6+4.8
- GDPValDeepSeek-V4-Flash by 3.246.943.7+3.2
ReasoningEven
- ARC-AGI-2DeepSeek-V4-Flash by 38.661.422.8+38.6
- SimpleBenchGLM-5.2 by 12.546.358.8+12.5
- LiveBench · ReasoningDeepSeek-V4-Flash by 886.678.6+8
- CritPtGLM-5.2 by 4.316.620.9+4.3
- Humanity's Last ExamGLM-5.2 by 2.538.641.1+2.5
- GPQA DiamondDeepSeek-V4-Flash by 1.390.889.5+1.3
FactsEven
- AA-Omniscience · Non-hallucinationGLM-5.2 by 65.48.373.7+65.4
- AA-Omniscience · AccuracyDeepSeek-V4-Flash by 16.140.424.3+16.1
- SimpleQA Verifiedtie34.134.2tie
MathGLM-5.2
- FrontierMath Tier 4GLM-5.2 by 4.924.429.3+4.9
- AIME 2026GLM-5.2 by 3.495.899.2+3.4
- LiveBench · MathematicsGLM-5.2 by 386.889.8+3
- IMOAnswerBenchGLM-5.2 by 2.688.491+2.6
- HMMT Feb. 2026DeepSeek-V4-Flash by 2.394.892.5+2.3
- FrontierMath Tiers 1-3 (v2)GLM-5.2 by 1.757.559.2+1.7
Long documentsDeepSeek-V4-Flash
- AA-LCRDeepSeek-V4-Flash by 1.479.778.3+1.4
Following instructionsDeepSeek-V4-Flash
- IFBenchDeepSeek-V4-Flash by 5.979.273.3+5.9
- LiveBench · Instruction FollowingDeepSeek-V4-Flash by 3.265.562.3+3.2
Other results25 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.
- GDPval-AA v2GLM-5.2 by 319 rating points11891508+319 rating
- ToolathlonDeepSeek-V4-Flash by 22.170.348.2+22.1
- AA-OmniscienceGLM-5.2 by 18.7-14.34.4+18.7
- AutomationBench PublicDeepSeek-V4-Flash by 12.225.112.9+12.2
- ARC-AGI-1DeepSeek-V4-Flash by 128977+12
- DeepSWE 1.1DeepSeek-V4-Flash by 10.454.444+10.4
- Toolathlon VerifiedDeepSeek-V4-Flash by 10.470.359.9+10.4
- HLE (with tools)GLM-5.2 by 9.645.154.7+9.6
- HLE (wo / w tools)GLM-5.2 by 9.645.154.7+9.6
- SWEBench Pro PublicGLM-5.2 by 9.552.662.1+9.5
- DeepSWEDeepSeek-V4-Flash by 8.254.446.2+8.2
- DSBench-FullStackDeepSeek-V4-Flash by 6.968.761.8+6.9
- livebench_data_analysisDeepSeek-V4-Flash by 5.679.373.7+5.6
- NL2RepoDeepSeek-V4-Flash by 5.354.248.9+5.3
- DSBench-HardDeepSeek-V4-Flash by 5.159.654.5+5.1
- τ²-Bench Telecom (AA run)GLM-5.2 by 4.19599.1+4.1
- τ³-Bench BankingGLM-5.2 by 3.922.926.8+3.9
- livebench_languageDeepSeek-V4-Flash by 379.276.2+3
- AA Agentic IndexDeepSeek-V4-Flash by 2.341.739.4+2.3
- JobBenchGLM-5.2 by 2.141.343.4+2.1
- Agents' Last ExamDeepSeek-V4-Flash by 1.425.223.8+1.4
- StrongREJECTGLM-5.2 by 1.197.498.5+1.1
- AA Intelligencetie34.333.7tie
- CyberGymtie76.777.2tie
- Artificial Analysis Coding Indextie69.168.8tie
Questions people ask
Which is better, DeepSeek-V4-Flash or GLM-5.2?
DeepSeek-V4-Flash wins three of the seven areas where both have results: agents, long documents and following instructions. GLM-5.2 wins coding and math. They are level on reasoning and facts.
Which is better for coding?
GLM-5.2. It wins 5 of the 7 coding tests both models report; DeepSeek-V4-Flash wins none, and 2 are ties.
Which is cheaper?
DeepSeek-V4-Flash costs $0.44 per million input tokens and $1.32 per million output tokens; GLM-5.2 costs $1.40 and $4.40. That makes DeepSeek-V4-Flash about 70% cheaper for the same work.
How do you compare the two?
We use the 55 benchmark tests both models have published scores on. The verdict counts the 30 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 25 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.