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Compare performance benchmarks, coding intelligence, reasoning evaluations, context limits, and API economics between GLM 5.2 (Zhipu AI) and Beam 1.0 501B A23B (Reflection AI).
| Metric / Capability | GLM 5.2 | Beam 1.0 501B A23B |
|---|---|---|
| Developer / Organization | Zhipu AI | Reflection AI |
| Release Date | 2026-06-16 | 2026-10-16 |
| Deployment / Weights | Open Weights | Open Weights |
| Context Window | 1.0M tokens (1,048,576 tokens) | 1.0M tokens (1,048,576 tokens) |
| Input Pricing (/1M Tokens) | Free (Open Weights) | Free (Open Weights) |
| Output Pricing (/1M Tokens) | Free (Open Weights) | Free (Open Weights) |
| Benchmark / Domain | GLM 5.2 | Beam 1.0 501B A23B | Advantage |
|---|---|---|---|
Artificial Analysis Intelligence Index Composite index aggregating 10+ evaluations of general reasoning and knowledge. | 33.7% | — | — |
Artificial Analysis Coding Index Composite index of coding and software-engineering evaluations. | 68.8% | — | — |
Artificial Analysis Agentic Index Composite index of tool-use and long-horizon agentic tasks. | 38.4% | — | — |
SWE-bench Pro Harder, contamination-resistant successor to SWE-bench spanning multiple languages. | 62.1% | 66.1% | Beam 1.0 501B A23B (+6%) |
ARC-AGI-2 Novel visual grid puzzles requiring abstract rule induction. | 22.8% | — | — |
GPQA Diamond Graduate-level physics, chemistry, and biology questions written by domain experts. | 91.2% | 90.6% | GLM 5.2 (+1%) |
Humanity's Last Exam Expert-written questions across hundreds of disciplines designed to resist saturation. | 40.5% | 36.0% | GLM 5.2 (+13%) |
FrontierMath v2 (Tiers 1-3) Unpublished, research-level mathematics problems across Tiers 1-3. | 59.2% | — | — |
Design Arena ELO Human-preference ELO across UI, 3D, data-visualization, and game-dev generations. | 1291 | 1227 | GLM 5.2 (+5%) |
GLM 5.2 leads across 3 evaluated benchmarks compared to 1 for Beam 1.0 501B A23B, showing notable advantages in GPQA Diamond, Humanity's Last Exam, Design Arena ELO.
Both models feature equivalent context windows of 1.0M tokens (1,048,576 tokens).
Both models have comparable pricing structures or open weight deployment options.
GLM 5.2 is an open-weights model. Beam 1.0 501B A23B is an open-weights model.
Analyze 130+ models side-by-side using interactive radar charts, cost-efficiency quadrant plots, and live dataset filters on the full NeuBench index.
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