Compare
Glm 4 32b 0414 vs Qwen2 1 5b
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.
Qwen2 1 5b has about 1× the context window of the other in this pair.
Qwen2 1 5b has 2% more context capacity (32K vs 32K tokens). Qwen2 1 5b is 96% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Qwen2 1 5b. Its 32K context fits entire documents without chunking (vs 32K).
RAG / high-volume retrieval
Use Qwen2 1 5b. Input tokens are 96% cheaper — critical when sending large retrieved contexts.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Glm 4 32b 0414 | Qwen2 1 5b |
|---|---|---|
| Context window | 32,000 tokens (32K) | 32,768 tokens (32K) |
| Max output tokens | 32,000 tokens (32K) | N/A |
| Speed tier | Balanced | Balanced |
| Vision | No | No |
| Function calling | Yes | No |
| Extended thinking | No | No |
| 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 in | Glm 4 32b 0414 out | Qwen2 1 5b in | Qwen2 1 5b out |
|---|---|---|---|---|
| Novita | $0.550/M | $1.66/M | — | — |
| Together Ai | — | — | $0.020/M | $0.020/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