GLM-5.2: Price, Context, Benchmarks, and Release Details
65.7
SI Score (method si-v2-absolute-shrinkage-1)
#30 of 115 ranked
100% confidence 100 percent, Full confidence — 5 of 7 expected sources in
Coverage 81% of expected source weight · 100% confidence at 80% coverage
Pillar breakdown
Coding (weight 40 percent) 66.2
Math (weight 15 percent) 70.4
Preference (weight 15 percent) 79.4
Reasoning (weight 30 percent) 68.3
Pillar weights: reasoning 30% · math 15% · coding 40% · preference 15%. Benchmark results use fixed 0–100 scales before averaging; incomplete evidence is shrunk toward 50.
Facts
- Input price / 1M
- not yet reported
- Output price / 1M
- not yet reported
- Context window
- 1Mmodels.devPublished source fact
Retrieved Oct 8, 2026 · MIT
Open source ↗ - Max output
- 131Kmodels.devPublished source fact
Retrieved Oct 8, 2026 · MIT
Open source ↗ - Released
- Jun 13, 2026models.devPublished source fact
Retrieved Oct 8, 2026 · MIT
Open source ↗ - Open weights
- Yesmodels.devPublished source fact
Retrieved Oct 8, 2026 · MIT
Open source ↗ - License
- not yet reported
- Input modalities
- textmodels.devPublished source fact
Retrieved Oct 8, 2026 · MIT
Open source ↗
Benchmark results
38 results| Benchmark | Raw result | Normalized (0–100) | Pillar |
|---|---|---|---|
| arc agi v1 public eval | 80.4%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] glm-5.2Published Oct 6, 2026
Retrieved Oct 8, 2026 · factual citation Open source ↗ | 80.4 | reasoning |
| arc agi v1 semi private | 77%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] glm-5.2Published Oct 6, 2026
Retrieved Oct 8, 2026 · factual citation Open source ↗ | 77.0 | reasoning |
| arc agi v2 public eval | 20.8%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] glm-5.2Published Oct 6, 2026
Retrieved Oct 8, 2026 · factual citation Open source ↗ | 20.8 | reasoning |
| arc agi v2 semi private | 22.8%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] glm-5.2Published Oct 6, 2026
Retrieved Oct 8, 2026 · factual citation Open source ↗ | 22.8 | reasoning |
| frontiermath tier 4 v2 | 29.3%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] maxPublished Jun 19, 2026
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 29.3 | math |
| frontiermath tiers 1 3 v2 | 54.7%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] lowPublished Aug 29, 2026
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 54.7 | math |
| frontiermath tiers 1 3 v2 | 59.2%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] maxPublished Jun 19, 2026
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 59.2 | math |
| frontiermath tiers 1 3 v2 | 42.5%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 29, 2026
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 42.5 | math |
| gpqa diamond | 87.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] lowPublished Aug 10, 2026
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 87.9 | reasoning |
| gpqa diamond | 91.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] maxPublished Jun 24, 2026
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 91.9 | reasoning |
| gpqa diamond | 71.2%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 10, 2026
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 71.2 | reasoning |
| gpqa diamond | 91.2%Official model cards via models.devLab-reported; metric accuracy; transcribed by MIT models.dev catalog; not independently evaluated [variant] Published Jun 16, 2026
Retrieved Oct 8, 2026 · factual citation; MIT transcription Open source ↗ | 91.2 | reasoning |
| hle text only subset | 40.5%Official model cards via models.devLab-reported; metric accuracy; transcribed by MIT models.dev catalog; not independently evaluated [variant] text-only subsetPublished Jun 16, 2026
Retrieved Oct 8, 2026 · factual citation; MIT transcription Open source ↗ | 40.5 | reasoning |
| hle text only subset tools | 54.7%Official model cards via models.devLab-reported; metric accuracy; transcribed by MIT models.dev catalog; not independently evaluated [variant] with tools; text-only subsetPublished Jun 16, 2026
Retrieved Oct 8, 2026 · factual citation; MIT transcription Open source ↗ | 54.7 | reasoning |
| livebench coding code completion 2026_06_25 | 80.4%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 80.4 | coding |
| livebench coding code generation 2026_06_25 | 78.9%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 78.9 | coding |
| livebench coding javascript 2026_06_25 | 63.6%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 63.6 | coding |
| livebench coding python 2026_06_25 | 55%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 55.0 | coding |
| livebench coding typescript 2026_06_25 | 36.7%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 36.7 | coding |
| livebench math amps hard 2026_06_25 | 98%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 98.0 | math |
| livebench math integrals with game 2026_06_25 | 76%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 76.0 | math |
| livebench math math comp 2026_06_25 | 96.1%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 96.1 | math |
| livebench math olympiad 2026_06_25 | 89.0%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 89.0 | math |
| livebench math simplify 2026_06_25 | 55.7%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 55.7 | math |
| livebench reasoning connections 2026_06_25 | 94%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 94.0 | reasoning |
| livebench reasoning consecutive events 2026_06_25 | 79.3%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 79.3 | reasoning |
| livebench reasoning logic with navigation 2026_06_25 | 80%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 80.0 | reasoning |
| livebench reasoning spatial 2026_06_25 | 94%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 94.0 | reasoning |
| livebench reasoning theory of mind 2026_06_25 | 75%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 75.0 | reasoning |
| livebench reasoning zebra puzzle 2026_06_25 | 65.5%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 8, 2026 · factual citation; Apache-2.0 code Open source ↗ | 65.5 | reasoning |
| lmarena text | 1470.4 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 2, 2026
Retrieved Oct 8, 2026 · CC-BY-4.0 Open source ↗ | 79.4 | preference |
| otis mock aime 2024 2025 | 75.6%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] lowPublished Aug 10, 2026
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 75.6 | math |
| otis mock aime 2024 2025 | 86.4%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] maxPublished Jun 25, 2026
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 86.4 | math |
| otis mock aime 2024 2025 | 28.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 10, 2026
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 28.9 | math |
| swe bench pro | 62.1%Official model cards via models.devLab-reported; metric resolve rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] Published Jun 16, 2026
Retrieved Oct 8, 2026 · factual citation; MIT transcription Open source ↗ | 62.1 | coding |
| swe bench verified | 78.7%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] maxPublished Jun 25, 2026
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 78.7 | coding |
| terminal bench v2 1 | 82.7%Official model cards via models.devLab-reported; metric success rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] Claude Code; 2.1Published Jun 16, 2026
Retrieved Oct 8, 2026 · factual citation; MIT transcription Open source ↗ | 82.7 | coding |
| terminal bench v2 1 | 81%Official model cards via models.devLab-reported; metric success rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] Terminus 2; 2.1Published Jun 16, 2026
Retrieved Oct 8, 2026 · factual citation; MIT transcription Open source ↗ | 81.0 | coding |
Normalization uses fixed absolute 0–100 scales for each unit, independently of other models that have a result on each benchmark. Coverage and evidence breadth still affect the composite; compare the evaluation conditions before reading a small score gap as decisive. “lab-reported” marks the provider's own published figure.
Sources: in and pending
in Reported (5)
- ARC Prize · arrived Oct 8, 2026
- Epoch AI Benchmarking · arrived Oct 8, 2026
- Official model cards via models.dev · arrived Oct 8, 2026
- LiveBench · arrived Oct 8, 2026
- LMArena / Arena · arrived Oct 8, 2026
pending Awaiting (2)
- Humanity’s Last Exam · carries 13% of expected weight
- Terminal-Bench · carries 6% of expected weight
The confidence % rises as pending sources publish. Some sources never cover some models — that is why 100% confidence arrives at 80% of expected weight, not at full coverage.