Compare / head-to-head
GLM-4.7-FlashXvsGPT-5.2
GLM-4.7-FlashX and GPT-5.2 do not yet share a public benchmark, so quality cannot be compared apples-to-apples. GLM-4.7-FlashX is 33.5x cheaper per token. GPT-5.2 has the larger context window (400K tokens).
Benchmarks from cited public sources; pricing from official pages; status from official provider feeds.
Shared benchmarks
0
no overlap yet
Cheaper per token
GLM-4.7-FlashX
33.5x cheaper, input + output
Larger context
GPT-5.2
400K tokens
Provider uptime (30d)
— · 94.7368%
Z.ai · OpenAI
GLM-4.7-FlashX
Z.ai
text
Quality
Benchmark matrix
0 shared · 0 only GLM-4.7-FlashX · 14 only GPT-5.2| Benchmark | GLM-4.7-FlashX | GPT-5.2 | Δ | Edge |
|---|---|---|---|---|
| Reported by both · 0 | ||||
| No public benchmark is reported for both models yet. | ||||
| Only GLM-4.7-FlashX reports · 0 | ||||
| GLM-4.7-FlashX reports nothing GPT-5.2 does not. | ||||
| Only GPT-5.2 reports · 14 | ||||
| SWE-bench Verified | not reported | 80% ↗ | — | — |
| GPQA Diamond | not reported | 92.4% ↗ | — | — |
| AIME 2025 | not reported | 100% ↗ | — | — |
| AIME 2026 | not reported | 98.3% ↗matharena | — | — |
| LMArena Elo | not reported | 1412.4 ↗ | — | — |
| ARC-AGI-1 (Verified) | not reported | 86.2% ↗ | — | — |
| ARC-AGI-2 (Verified) | not reported | 52.9% ↗ | — | — |
| FrontierMath Tier 4 v2 (Epoch AI run) | not reported | 31.7% ↗epoch | — | — |
| FrontierMath Tiers 1-3 v2 (Epoch AI run) | not reported | 67.4% ↗epoch | — | — |
| GDPval (wins or ties) | not reported | 70.9% ↗ | — | — |
| OTIS Mock AIME 2024-2025 (Epoch AI run) | not reported | 96.1% ↗epoch | — | — |
| SimpleQA Verified | not reported | 37.1% ↗epoch | — | — |
| SWE-Bench Pro | not reported | 55.6% ↗ | — | — |
| SWE-bench Verified (Epoch AI run) | not reported | 73.8% ↗epoch | — | — |
Scores tagged "epoch" or "matharena" are independent runs, used only where the lab has not published its own; ⚠ marks rows MathArena flags as released after the competition. Higher is better on every row. Δ is GLM-4.7-FlashX minus GPT-5.2 in the benchmark's own unit. "Not reported" means the lab has not published that figure; it is not a zero. ↗ opens the source.
Specs & pricing
Side by side
Official pricing pages and model cards| Spec | GLM-4.7-FlashX | GPT-5.2 | Edge |
|---|---|---|---|
| Context window | 200K tokens | 400K tokens | GPT-5.2 |
| Max output | 131K tokens | 128K tokens | GLM-4.7-FlashX |
| Input price / 1M | $0.07 ↗ | $1.75 ↗ | GLM-4.7-FlashX |
| Output price / 1M | $0.4 ↗ | $14 ↗ | GLM-4.7-FlashX |
| Cached input / 1M | $0.01 ↗ | $0.175 ↗ | GLM-4.7-FlashX |
| Input + output / 1M Lower is cheaper. List prices; batch, tool and regional fees excluded. | $0.47 | $15.75 | GLM-4.7-FlashX |
| Modalities | text | text · vision | GPT-5.2 |
| Released | — | 2025-12-11 | — |
| Cited benchmark scores | 0 | 16 | — |
Reliability
Provider status
Last 60 days · refreshed daily on this page · live on /statusMore matchups
GPT-5.2 vs …
Models sharing the most benchmarksBuilt by Respan
Which one wins on your data?
Public benchmarks are a starting point. Run GLM-4.7-FlashX and GPT-5.2 on your own prompts with Respan evals, or route to either through one gateway key with automatic failover.