Model crosswalk
Side-by-side on price, capability and workload — three-way comparison.
Granite 3.1 2B Instruct
vs
Llama 3.2 1B Instruct
vs
Llama 3.2 3B Instruct
Granite 3.1 2B InstructA
Granite 3.1 2B Instruct
2B params · 131K context · apache-2.0
Cheapest provider—
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Llama 3.2 1B InstructB
Llama 3.2 1B Instruct
1B params · 131K context · llama-3
Cheapest provider—
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Llama 3.2 3B InstructC
Llama 3.2 3B Instruct
3B params · 131K context · llama-3
Cheapest provider—
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Specs and cheapest providers
| Spec | Granite 3.1 2B Instruct | Llama 3.2 1B Instruct | Llama 3.2 3B Instruct |
|---|---|---|---|
| Parameters | 2B | 1B | 3B |
| Context window | 131K tokens | 131K tokens | 131K tokens |
| License | apache-2.0 | llama-3 | llama-3 |
| Released | 2024-12-19 | 2024-09-25 | 2024-09-25 |
| Cheapest provider | |||
| Provider | — | — | — |
| Input / 1M tokens | — | — | — |
| Output / 1M tokens | — | — | — |
Benchmark comparison
No benchmark data available yet.
Editor's take
IBM's enterprise-extraction 2B sits alongside Meta's two smallest Llama models — a comparison that's really about context depth, use-case focus, and how much quality ceiling you need.
Granite 3.1 2B Instruct is IBM's smallest production model from the Granite 3 series, running 2 billion parameters with a 128K context window. That context length at 2B scale is unusual — Llama 3.2 3B and Gemma 2 2B both cap lower. IBM built Granite 3 for enterprise compliance workflows, structured extraction, and tool-calling rather than generative tasks. Long-document classification pipelines that would normally require a larger model often run acceptably on Granite 3.1 2B. Apache 2.0 license makes commercial deployment frictionless. Primary hosting on IBM watsonx.ai with growing third-party provider availability.
Llama 3.2 1B Instruct is Meta's smallest Llama variant, released September 2024 with 1 billion parameters targeting on-device mobile and edge inference. The quality ceiling is low: at 1B parameters, summarization, code, and multi-step reasoning produce unreliable outputs. The model's value is constrained-hardware deployment and sub-$0.05 per million token pricing on hosted providers. The 131K context window is present but rarely the binding consideration at this quality level. Llama 3 community license permits commercial use.
Llama 3.2 3B Instruct, also released September 2024, is the next step up — still designed for edge and on-device use but with a meaningful quality uplift over the 1B. Classification, short-form summarization, and content moderation routing are viable at this tier. Hosted pricing typically runs below $0.10 per million tokens, making it the go-to for volume-heavy quality-tolerant pipelines. The 131K context is retained, and the Llama 3 community license applies.
Pick Granite 3.1 2B for enterprise structured extraction, long-document classification, and tool-calling with Apache 2.0 licensing. Pick Llama 3.2 1B for on-device mobile inference where memory is the hard constraint. Pick Llama 3.2 3B for hosted volume workloads — classification and routing tasks — where 1B quality is insufficient but 8B cost is unwarranted.
Compare two at a time
Frequently asked questions
- How does Granite 3.1 2B Instruct compare to Llama 3.2 1B Instruct and Llama 3.2 3B Instruct on price?
- Use the table above to compare input and output prices per 1M tokens across the cheapest available providers for each model.
- Which model is best for coding: Granite 3.1 2B Instruct, Llama 3.2 1B Instruct, or Llama 3.2 3B Instruct?
- HumanEval and other code benchmarks are shown in the table. For production code tasks, also consider context window size and provider latency.
- What is the context window for Granite 3.1 2B Instruct, Llama 3.2 1B Instruct, and Llama 3.2 3B Instruct?
- Context window sizes are listed in the Specs row of the comparison table above.
Full model details