Head-to-head
GLM 5.1 vs GPT-5.5 Pro
Compare GLM 5.1 and GPT-5.5 Pro on the metrics that decide an agent workload.
| Metric | GLM 5.1 | GPT-5.5 Pro |
|---|---|---|
| Provider | Fireworks AI | OpenAI |
| Input / 1M | $1.40 | $30.00 |
| Output / 1M | $4.40 | $180.00 |
| Cache read / 1M | $0.26 (−81%) | $30.00 (−0%) |
| Reuse-adj @55% | $1.68 | $67.50 |
| Context | 203K | 1.1M |
| Cache capture | 83% | 80% |
| Warm TTFT | 130ms (−62%) | 900ms (−53%) |
| Quality index | 89 | 86 |
Teal marks the better value in each row. Reuse-adjusted assumes 55% prefix reuse and a 25% output share.
Pick GLM 5.1 when it scores higher on the composite quality index, it is cheaper once prefix reuse is priced in, it answers faster on warm cache hits.
Pick GPT-5.5 Pro when it carries the larger 1.1M context window.
GLM 5.1 wins on both reuse-adjusted cost and quality here, so it is the default pick. Reach for GPT-5.5 Pro only when a specific constraint (modality, latency floor, or licensing) forces it.
Frequently asked
GLM 5.1 vs GPT-5.5 Pro, answered.
Is GLM 5.1 or GPT-5.5 Pro cheaper?
At 55% prefix reuse, GLM 5.1 blends to about $1.68 per 1M tokens and GPT-5.5 Pro to about $67.50. GLM 5.1 is cheaper on that basis.
Which has the larger context window?
GPT-5.5 Pro has the larger window: 1.1M vs 203K tokens.
Which captures more reuse?
GLM 5.1 shows higher measured cache capture (83% 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.