Compare
Granite 4 H Small vs Olmo 3 32B Think
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.
Olmo 3 32B Think has about 3.2× the context window of the other in this pair.
Olmo 3 32B Think has 220% more context capacity (65K vs 20K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Olmo 3 32B Think. Its 65K context fits entire documents without chunking (vs 20K).
Long output (reports, code files)
Use Olmo 3 32B Think. Its 65K 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 | Granite 4 H Small | Olmo 3 32B Think |
|---|---|---|
| Context window | 20,480 tokens (20K) | 65,536 tokens (65K) |
| Max output tokens | 20,480 tokens (20K) | 65,536 tokens (65K) |
| Speed tier | Balanced | Deep |
| Vision | No | No |
| Function calling | Yes | No |
| Extended thinking | No | Yes |
| Prompt caching | No | No |
| Batch API | No | No |
| Release date | N/A | Nov 2025 |
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 | Granite 4 H Small in | Granite 4 H Small out | Olmo 3 32B Think in | Olmo 3 32B Think out |
|---|---|---|---|---|
| Ibm Watsonx | $0.060/M | $0.250/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