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GLM 5.2 vs GPT-6.1 Terra

Full profiles: GLM 5.2 (Zhipu AI) and GPT-6.1 Terra (OpenAI): every benchmark, price and rank.

Updated · Data from 6 sources

As of 27 Oct 2026, GLM 5.2 (max) and GPT-6.1 Terra (max) are neck and neck on quality (62.2 vs 65.9, inside the ±7.8 margin of error) and close on price, so pick on the category that matters to you. GPT-6.1 Terra leads in every category we measure both in.

GLM 5.2 benchmarks max Zhipu AI GPT-6.1 Terra benchmarks max OpenAIOpen in the comparison tool

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use casePickWhyConfidence
ReasoningGPT-6.1 Terra86 vs 70 category score; CritPt 28.0% vs 20.9%High
KnowledgeGPT-6.1 Terra75 vs 54 category score; AA-Omniscience 29.8 vs 4.4High
Long documentsGPT-6.1 Terra66 vs 64 category score; AA-LCR 82.7% vs 78.3%Medium
Chat quality (human preference)–Only GLM 5.2 has an Arena rating (67 category score)Not comparable
Lowest costEither$2.15 vs $2.00 per 1M blended; agentic coding session $0.102 vs $0.080–
Fastest first answerGLM 5.224.8 s (GLM 5.2 (max)) vs 131.8 s (GPT-6.1 Terra (max)) to the first answer token–
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • GLM 5.2 (max) and GPT-6.1 Terra (max) are neck and neck on quality (62.2 vs 65.9, within the ±7.8 margin).
  • GLM 5.2 (max) is stronger in agents & tools, coding, human preference, instruction following, maths.
  • GPT-6.1 Terra (max) is stronger in composite, knowledge, long context, reasoning, multimodal.
  • They cost about the same ($2.00 per 1M blended).

At a glance

SpecGLM 5.2GPT-6.1 Terra
DeveloperZhipu AIOpenAI
Released16 Jun 202626 Oct 2026
Context window (tokens)1,000,0001,050,000
Compared atGLM 5.2 (max)GPT-6.1 Terra (max)
Open weightsYesNo
Price in / out / cached input per 1M$1.40 / $4.40 / $0.299$1.00 / $5.00 / $0.050

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

CategoryGLM 5.2 (max)GPT-6.1 Terra (max)Leader
Reasoning69.586.2GPT-6.1 Terra
Coding62.2–not comparable
Agents & tools62.6–not comparable
Maths57.3–not comparable
Knowledge53.574.5GPT-6.1 Terra
Instruction following71.7–not comparable
Human preference66.6–not comparable
Multimodal–67.5not comparable
Long context64.066.3GPT-6.1 Terra
Composite66.882.8GPT-6.1 Terra

Where sources disagree

Across the 11 benchmarks both have, GLM 5.2 leads 1, GPT-6.1 Terra leads 10. Every overall index that rates both puts GPT-6.1 Terra ahead.

Overall indexGLM 5.2 (max)GPT-6.1 Terra (max)Leader
BenchLeader Index62.265.9neck and neck
AA Intelligence Index v4.3.233.748.1GPT-6.1 Terra

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.

MeasureGLM 5.2 (max)GPT-6.1 Terra (max)
Blended price per 1M tokens$2.15$2.00
Input / output per 1M$1.40 / $4.40$1.00 / $5.00
Cached input per 1M$0.299$0.050
Price per task: chat reply$0.0019$0.0019
Price per task: summarize a 30-page report$0.019$0.015
Price per task: code edit$0.015$0.013
Price per task: agentic coding session$0.102$0.080
Price per task: structured extraction$0.0037$0.0030
Cost to run a full benchmark suite$1.28$0.403
Output speed94 tok/s91 tok/s
Time to first answer24.8 s131.8 s
Time to a complete answer30.1 s137.3 s

Per token is not per task: on Artificial Analysis' full suite GLM 5.2 (max) cost $1.28 and GPT-6.1 Terra (max) $0.403, because GLM 5.2 (max) used about 3.0× as many tokens for the same work, which a per-token price hides.

Each model is compared at its best-ranked reasoning-effort setting. GLM 5.2 (max) scores 62.2 and takes 25 s to its first answer token; GLM 5.2 scores 51.8 in 0 s, GLM 5.2 (no reasoning) scores 47.9 in 1 s. GPT-6.1 Terra (max) scores 65.9 and takes 132 s to its first answer token; GPT-6.1 Terra (xhigh) scores 65.0 in 18 s, GPT-6.1 Terra (high) scores 64.7 in 7 s. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

111 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

MetricPublisherGLM 5.2 (max)GPT-6.1 Terra (max)
BenchLeader IndexBenchLeader62.265.9
Agents & tools scoreBenchLeader62.6–
Coding scoreBenchLeader62.2–
Composite scoreBenchLeader66.882.8
Human preference scoreBenchLeader66.6–
Instruction following scoreBenchLeader71.7–
Knowledge scoreBenchLeader53.574.5
Long context scoreBenchLeader64.066.3
Maths scoreBenchLeader57.3–
Reasoning scoreBenchLeader69.586.2
Multimodal scoreBenchLeader–67.5
Blended price $/MBenchLeader$2.15$2.00
Output speedBenchLeader94 tok/s91 tok/s
Time to first answerBenchLeader24.8 s131.8 s
Context windowBenchLeader1,000,000 tokens1,050,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub91.9%–
SimpleBenchSimpleBench58.8%†–
Arena Hard PromptsArena (LMArena)1496–
LiveBench 2.0 ReasoningLiveBench–88.7%†
LiveBench 1.0 ReasoningLiveBench78.6%†–
GPQA Diamond (AA)Artificial Analysis89.5%–
Humanity's Last Exam (AA)Artificial Analysis41.1%46.3%
GPQA Diamond (Vals)Vals AI85.6%†–
Kagi LLM BenchmarkKagi LLM Benchmark62.6%†–
ARC-AGI-1ARC Prize77.0%†–
ARC-AGI-2ARC Prize22.8%†–
CritPtArtificial Analysis20.9%28.0%
Chess PuzzlesEpoch AI Benchmarking Hub22.0%–
Mystery Game PuzzlesEpoch AI Benchmarking Hub18.0%†–
LMCAEpoch AI Benchmarking Hub45.8%–
DTBenchEpoch AI Benchmarking Hub93.6%–
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub78.7%–
SciCodeSciCode51.2%–
WeirdMLWeirdML70.1%–
FrontierCodeCognition24.5%†–
Arena CodingArena (LMArena)1514–
Arena WebDevArena (LMArena)1604–
LiveBench 2.0 CodingLiveBench–90.8%†
LiveBench 1.0 CodingLiveBench79.7%†–
SciCode (AA)Artificial Analysis51.2%55.1%
Show all 111 benchmarks
MetricPublisherGLM 5.2 (max)GPT-6.1 Terra (max)
Coding
LiveCodeBenchVals AI69.5%†–
SWE-bench (Vals)Vals AI82.8%–
Code MigrationVals AI37.9%–
ProgramBenchVals AI0.5%–
Vibe Code Bench v1.1Vals AI64.0%–
SWE Atlas: Codebase QnAScale AI SEAL48.1%†–
SWE Atlas: RefactoringScale AI SEAL42.4%†–
SWE Atlas: Test WritingScale AI SEAL41.5%†–
Surface Evolver BenchEpoch AI Benchmarking Hub55.6%†–
DeepSWE v1.1Epoch AI Benchmarking Hub43.8%–
ALE-BenchEpoch AI Benchmarking Hub1010.2–
Terminal-Bench 4.0 (AA)Artificial Analysis1.0%55.6%
Terminal-Bench 2.1 (AA)Artificial Analysis77.9%–
Startrise FrontendStartrise72.1%†–
FrontierCode 1.1 (AA)Artificial Analysis–36.0%
Agents & tools
APEX-AgentsMercor45.2%†–
Arena AgentArena (LMArena)1.7–
LiveBench Long AgenticLiveBench–48.6%†
LiveBench BrowserLiveBench–93.1%†
LiveBench Agentic CodingLiveBench51.8%†–
Terminal-Bench HardArtificial Analysis50.8%–
τ²-Bench Telecom (AA)Artificial Analysis99.1%–
Terminal-Bench 2.1 (Vals)Vals AI67.8%–
MCP AtlasScale AI SEAL77.8%†–
HiL-BenchScale AI SEAL43.7%†–
τ³-bench Bankingτ²-bench37.1%†–
τ³-Banking (AA)Artificial Analysis34.6%–
ITBench SRE (AA)Artificial Analysis42.7%–
APEX-Agents (AA)Artificial Analysis33.7%–
Finance Agent v2Vals AI49.7%†–
Harvey's Legal Agent Benchmark v1Vals AI7.1%–
Legal Research BenchVals AI31.3%–
SkillsBenchVals AI45.1%–
SREBenchVals AI0.0%–
PostTrainBenchEpoch AI Benchmarking Hub31.7%–
GBAEvalEpoch AI Benchmarking Hub0.0%†–
Vending-Bench 2Andon Labs8313.8†–
AutomationBenchArtificial Analysis28.4%60.2%
GDP.pdf (AA)Artificial Analysis10.4%28.6%
EnterpriseOps-GymArtificial Analysis42.7%–
AA-Briefcase v1.1Artificial Analysis12271402
Terminal-Bench-Science 0.1 (AA)Artificial Analysis–57.6%
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub59.2%–
FrontierMath Tier 4Epoch AI Benchmarking Hub29.3%–
OTIS Mock AIMEEpoch AI Benchmarking Hub86.4%–
ProofBenchVals AI35.0%–
LiveBench MathematicsLiveBench89.8%†–
AIME 2026MathArena90.0%†–
HMMT February 2026MathArena92.4%†–
MathArena ApexMathArena19.8%†–
Arena MathsArena (LMArena)1488–
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub34.2%–
LiveBench 2.0 Data AnalysisLiveBench–82.3%†
LiveBench ResearchLiveBench–73.9%†
LiveBench 1.0 Data AnalysisLiveBench73.7%†–
AA-OmniscienceArtificial Analysis4.429.8
MMLU-ProVals AI86.7%†–
LegalBenchVals AI84.1%†–
CorpFinVals AI66.1%†–
TaxEvalVals AI73.3%†–
Excel Modeling BenchmarkVals AI61.5%†–
MedCodeVals AI40.8%†–
MedScribeVals AI83.5%†–
DrugDiscoveryBenchScale AI SEAL36.2%†–
EBR-benchEpoch AI Benchmarking Hub9.5%–
AA-Omniscience: accuracyArtificial Analysis24.3%49.1%
AA-Omniscience: non-hallucinationArtificial Analysis73.7%62.0%
Instruction following
LiveBench LanguageLiveBench76.2%†–
LiveBench Instruction FollowingLiveBench62.3%†–
IFBenchArtificial Analysis73.3%–
Arena Instruction FollowingArena (LMArena)1469–
Human preference
Arena TextArena (LMArena)1475–
EQ-Bench 4EQ-Bench1211†–
Arena Creative WritingArena (LMArena)1453–
Arena Multi-turnArena (LMArena)1475–
Arena Longer QueriesArena (LMArena)1486–
Multimodal
LiveBench DesignLiveBench–82.3%†
MMMU-ProArtificial Analysis–84.7%
Long context
AA-LCRArtificial Analysis78.3%82.7%
MLCRArtificial Analysis12.8%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub151.9†–
LiveBench 2.0LiveBench–77.2%†
LiveBench 1.0LiveBench73.2%†–
AA Intelligence Index v4.3.2Artificial Analysis33.748.1
Safety & honesty
FORTRESSScale AI SEAL–18.2%†
Metadata
AA Openness IndexArtificial Analysis44.4–

Data as of 2026-10-27. Best configuration of each model; every score links to its source on the model pages.

What changed

  • GLM 5.2 (max): cached input price moved from $0.26/M to $0.30/M (15% up).
  • GLM 5.2 (max): cost per task moved from $1.47/M to $1.28/M (13% down); cached input price moved from $0.30/M to $0.26/M (13% down).
  • GLM 5.2 (max): 1 new result (AA-Briefcase v1.1); cached input price moved from $0.26/M to $0.30/M (15% up).
  • GLM 5.2 (max): cached input price moved from $0.30/M to $0.26/M (13% down).
  • GLM 5.2 (max): BenchLeader Index 62.8 → 62.3.
  • GLM 5.2 (max): 1 new result (Harvey's Legal Agent Benchmark v1).
  • GLM 5.2 (max): 1 score revision.
  • GLM 5.2 (max): cached input price moved from $0.26/M to $0.30/M (15% up).
  • GLM 5.2 (max): 4 new results (AutomationBench, GDP.pdf (AA), MLCR…).
  • GLM 5.2 (max): 1 new result (Harvey's Legal Agent Benchmark v1.1).

Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs

GLM 5.2 vs GPT-6.1 Terra: questions

Is GLM 5.2 better than GPT-6.1 Terra?
GLM 5.2 (max) and GPT-6.1 Terra (max) are neck and neck on quality (62.2 vs 65.9, within the ±7.8 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-27, so check the category scores for your use.
Which is cheaper, GLM 5.2 or GPT-6.1 Terra, and will that change?
GPT-6.1 Terra is cheaper today: $2.00 against $2.15 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Which is better for long documents?
GPT-6.1 Terra scores higher on long-context benchmarks (66 vs 64). Both take about 1.1M tokens: GLM 5.2 1,000,000, GPT-6.1 Terra 1,050,000.
Which has lower latency?
GLM 5.2 (max) answers first: 24.8 s against 131.8 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
Which is faster, GLM 5.2 or GPT-6.1 Terra?
GLM 5.2 streams faster: 94 against 91 output tokens per second.
Do independent benchmarks agree on GLM 5.2 vs GPT-6.1 Terra?
Across the 11 benchmarks both have, GLM 5.2 leads 1, GPT-6.1 Terra leads 10. Every overall index that rates both puts GPT-6.1 Terra ahead.
When was GPT-6.1 Terra released?
GPT-6.1 Terra was released on 26 Oct 2026.