DeepSeek-V4-Pro vs GLM 5.1
Compare DeepSeek-V4-Pro and GLM 5.1 on the metrics that decide an agent workload.
| Metric | DeepSeek-V4-Pro | GLM 5.1 |
|---|---|---|
| Provider | Fireworks AI | Fireworks AI |
| Input / 1M | $1.74 | $1.40 |
| Output / 1M | $3.48 | $4.40 |
| Cache read / 1M | $0.14 (−92%) | $0.26 (−81%) |
| Reuse-adj @55% | $1.52 | $1.68 |
| Context | 1M | 203K |
| Cache capture | 80% | 82% |
| Warm TTFT | 130ms (−63%) | 130ms (−62%) |
| Quality index | 88 | 86 |
Teal marks the better value in each row. Reuse-adjusted assumes 55% prefix reuse and a 25% output share.
Pick DeepSeek-V4-Pro when it scores higher on the composite quality index, it is cheaper once prefix reuse is priced in, it carries the larger 1M context window.
Pick GLM 5.1 when it captures more of the available reuse.
DeepSeek-V4-Pro wins on both reuse-adjusted cost and quality here, so it is the default pick. Reach for GLM 5.1 only when a specific constraint (modality, latency floor, or licensing) forces it.
DeepSeek-V4-Pro vs GLM 5.1, answered.
Is DeepSeek-V4-Pro or GLM 5.1 cheaper?
At 55% prefix reuse, DeepSeek-V4-Pro blends to about $1.52 per 1M tokens and GLM 5.1 to about $1.68. DeepSeek-V4-Pro is cheaper on that basis.
Which has the larger context window?
DeepSeek-V4-Pro has the larger window: 1M vs 203K tokens.
Which captures more reuse?
GLM 5.1 shows higher measured cache capture (82% vs 80%) in the Zumik corpus.
Let an alias pick for you.
Route to whichever model wins under current policy automatically. Zumik resolves the alias to the best fit per request, so you never hard-code a loser.