Compare / head-to-head
GLM-4.7-FlashXvsGLM-5-Turbo
GLM-4.7-FlashX and GLM-5-Turbo do not yet share a public benchmark, so quality cannot be compared apples-to-apples. GLM-4.7-FlashX is 11.1x cheaper per token. Both offer a 200K-token context window.
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
11.1x cheaper, input + output
Larger context
Tie
both 200K tokens
Provider uptime (30d)
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Z.ai
GLM-4.7-FlashX
Z.ai
text
GLM-5-Turbo
Z.ai
text
Quality
Benchmark matrix
0 shared · 0 only GLM-4.7-FlashX · 0 only GLM-5-Turbo| Benchmark | GLM-4.7-FlashX | GLM-5-Turbo | 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 GLM-5-Turbo does not. | ||||
| Only GLM-5-Turbo reports · 0 | ||||
| GLM-5-Turbo reports nothing GLM-4.7-FlashX does not. | ||||
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 GLM-5-Turbo 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 | GLM-5-Turbo | Edge |
|---|---|---|---|
| Context window | 200K tokens | 200K tokens | Tie |
| Max output | 131K tokens | 131K tokens | Tie |
| Input price / 1M | $0.07 ↗ | $1.2 ↗ | GLM-4.7-FlashX |
| Output price / 1M | $0.4 ↗ | $4 ↗ | GLM-4.7-FlashX |
| Cached input / 1M | $0.01 ↗ | $0.24 ↗ | GLM-4.7-FlashX |
| Input + output / 1M Lower is cheaper. List prices; batch, tool and regional fees excluded. | $0.47 | $5.2 | GLM-4.7-FlashX |
| Modalities | text | text | Tie |
| Released | — | — | — |
| Cited benchmark scores | 0 | 0 | — |
Reliability
Z.ai status
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Which one wins on your data?
Public benchmarks are a starting point. Run GLM-4.7-FlashX and GLM-5-Turbo on your own prompts with Respan evals, or route to either through one gateway key with automatic failover.