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GLM 5 Turbo vs Qwen3p7 Plus
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.
Model
Qwen3p7 Plus
Context window
262K
262,144 tokens · ~197K words
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.
Qwen3p7 Plus has about 1.3× the context window of the other in this pair.
Qwen3p7 Plus has 29% more context capacity (262K vs 202K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Qwen3p7 Plus. Its 262K context fits entire documents without chunking (vs 202K).
Long output (reports, code files)
Use GLM 5 Turbo. Its 131K 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 5 Turbo | Qwen3p7 Plus |
|---|---|---|
| Context window | 202,752 tokens (202K) | 262,144 tokens (262K) |
| Max output tokens | 131,072 tokens (131K) | 65,536 tokens (65K) |
| Speed tier | Balanced | Balanced |
| Vision | No | Yes |
| Function calling | Yes | Yes |
| Extended thinking | Yes | Yes |
| Prompt caching | Yes | Yes |
| Batch API | No | No |
| Release date | Mar 2026 | 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 5 Turbo in | GLM 5 Turbo out | Qwen3p7 Plus in | Qwen3p7 Plus out |
|---|---|---|---|---|
| Fireworks | — | — | $0.400/M | $1.60/M |
Frequently asked questions
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Use a smaller model.
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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