BenchLeader

GLM 5.3 vs Qwen3.8 Max

Verdict
  • GLM 5.3 (max) and Qwen3.8 Max (max) are level on quality (64.0 vs 64.2).
  • GLM 5.3 (max) is stronger in agents & tools, composite.
  • Qwen3.8 Max (max) is stronger in coding, human preference, knowledge, long context, maths, reasoning, multimodal.
  • GLM 5.3 (max) is 1.4× cheaper ($2.15 vs $3.00 per 1M blended).
  • GLM 5.3 (max) streams 2.3× faster (83 vs 37 tokens per second).
MetricGLM 5.3 (max)Qwen3.8 Max (max)
BenchLeader Index64.064.2
Agents & tools score61.358.2
Coding score62.164.6
Composite score80.370.7
Human preference score67.468.0
Knowledge score58.762.7
Long context score65.065.4
Maths score60.765.1
Reasoning score68.972.2
Multimodal score–66.2
Blended price $/M$2.15$3.00
Output speed83 tok/s37 tok/s
Time to first answer26.5 s58.9 s
Context window1M1M
GPQA Diamond90.9%–
FrontierMath Tiers 1–368.8%–
FrontierMath Tier 429.3%–
OTIS Mock AIME91.1%–
SimpleQA Verified41.0%–
Terminal-Bench41.8%27.0%
SciCode59.0%53.2%
WeirdML75.4%–
APEX-Agents–63.3%
FrontierCode40.1%–
ProofBench49.0%58.0%
Epoch Capabilities Index–156.4
LMArena Text14781483
LMArena Hard Prompts15041504
LMArena Coding15201524
LMArena WebDev16221672
LMArena Vision–1314
LMArena Agent2.12.3
LiveBench–78.5%
LiveBench Reasoning–88.2%
LiveBench Coding–72.9%
LiveBench Agentic Coding–64.7%
LiveBench Mathematics–91.3%
LiveBench Data Analysis–78.4%
LiveBench Language–79.7%
LiveBench Instruction Following–74.1%
AA Intelligence Index v4.3.244.845.4
AA-LCR79.7%80.3%
MMMU-Pro–82.8%
AA-Omniscience14.312.0
GPQA Diamond (AA)91.7%92.8%
Humanity's Last Exam (AA)42.3%43.1%
SciCode (AA)59.0%53.2%
LiveCodeBench80.5%87.8%
MMLU-Pro86.8%88.6%
IOI68.4%68.9%
LegalBench84.8%83.6%
CorpFin–65.8%
TaxEval72.4%75.5%
Terminal-Bench 2.1 (Vals)71.5%67.4%
SWE-bench (Vals)95.4%85.6%
GPQA Diamond (Vals)88.1%93.7%
Vals Index53.548.3
CritPt19.1%20.0%
GDPval-AA v2.157.5%58.6%
τ³-Banking (AA)50.3%51.3%
ITBench SRE (AA)46.1%40.3%
Analyst Agent (AA)–45.0%
APEX-Agents (AA)–42.4%
Code Migration44.2%24.0%
CyberBench72.1%28.6%
Excel Modeling Benchmark56.3%60.1%
Finance Agent v255.8%50.6%
Harvey's Legal Agent Benchmark8.3%10.4%
Legal Research Bench49.0%47.6%
MedCode42.9%40.7%
MedScribe88.8%85.0%
MMMU-Pro (Vals)–88.0%
MortgageTax–64.0%
MysteryMechanism23.0%23.9%
ProgramBench1.5%0.0%
Public Benefits Bench68.5%67.1%
SAGE–51.3%
SkillsBench47.5%42.0%
Tax Agent Bench73.1%66.0%
Terminal-Bench 4.0 (Vals)38.9%34.3%
Terminal-Bench Science4.3%1.4%
Vals Multimodal Index–65.4%
Vibe Code Bench 1-10020.0%12.8%
Vibe Code Bench v1.178.1%64.7%
FORTRESS28.2%–
LMArena Maths14921497
LMArena Creative Writing14541470
LMArena Instruction Following14751474
LMArena Multi-turn14811492
LMArena Longer Queries14851492
Chess Puzzles21.0%–
Mystery Game Puzzles33.0%–
DeepSWE v1.169.0%–
CursorBench42.6%–
FrontierSWE30.2%–
Terminal-Bench 4.0 (AA)41.9%38.9%
Terminal-Bench 2.1 (AA)83.9%88.8%
AutomationBench62.2%56.2%
GDP.pdf11.2%22.8%
MLCR48.3%20.0%
Harvey LAB0.3%–
EnterpriseOps-Gym36.4%47.6%
AA-Omniscience: accuracy33.9%31.9%
AA-Omniscience: non-hallucination70.5%71.2%
AA-Briefcase v1.115091617
AA Openness Index33.3–

Data as of 2026-10-11. Best configuration of each model; every score links to its source on the model pages.

GLM 5.3 vs Qwen3.8 Max: questions

Is GLM 5.3 better than Qwen3.8 Max?
GLM 5.3 (max) and Qwen3.8 Max (max) are level on quality (64.0 vs 64.2). The BenchLeader Index combines every independent quality benchmark; Qwen3.8 Max (max) is ahead overall as of 2026-10-11, but check the category scores for your use.
Is GLM 5.3 better than Qwen3.8 Max for coding?
Qwen3.8 Max scores higher in coding (65 vs 62 on the category index, where 50 is average).
Is GLM 5.3 better than Qwen3.8 Max for agentic tasks?
GLM 5.3 scores higher in agentic tasks (61 vs 58 on the category index, where 50 is average).
Which is cheaper, GLM 5.3 or Qwen3.8 Max?
GLM 5.3 is cheaper: $2.15 against $3.00 per million tokens, blended at three input tokens per output token.
Which is faster, GLM 5.3 or Qwen3.8 Max?
GLM 5.3 streams faster: 83 against 37 output tokens per second.
Which has the larger context window?
Both accept 1M tokens of context.