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Glm 4 32b 0414 128k vs Glm 4p5
This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.
Context window · side by side
Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.
Same context window size for both models.
Glm 4 32b 0414 128k and Glm 4p5 have identical context windows (128K tokens). Glm 4 32b 0414 128k is 81% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
RAG / high-volume retrieval
Use Glm 4 32b 0414 128k. Input tokens are 81% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Glm 4p5. Its 96K max output lets you generate complete artifacts in one request.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Glm 4 32b 0414 128k | Glm 4p5 |
|---|---|---|
| Context window | 128,000 tokens (128K) | 128,000 tokens (128K) |
| Max output tokens | 32,000 tokens (32K) | 96,000 tokens (96K) |
| Speed tier | Balanced | Balanced |
| Vision | No | No |
| Function calling | Yes | Yes |
| Extended thinking | No | Yes |
| Prompt caching | No | No |
| Batch API | No | No |
| Release date | N/A | N/A |
Pricing matrix
Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.
| Provider | Glm 4 32b 0414 128k in | Glm 4 32b 0414 128k out | Glm 4p5 in | Glm 4p5 out |
|---|---|---|---|---|
| Fireworks | — | — | $0.550/M | $2.19/M |
| Z Ai | $0.100/M | $0.100/M | — | — |
Frequently asked questions
Powered by Mem0
Use a smaller model.
Get better results.
Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.
Example: a multi-turn chat session
80% less to send — works with any model