Granite 4.2 30B vs GPT-5.2 Pro
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | Granite 4.2 30B | GPT-5.2 Pro |
|---|---|---|
| Developer | IBM | OpenAI |
| Family | Granite 4 2 | Gpt 5 2 |
| Model | Granite 4.2 30B | GPT-5.2 Pro |
| Version | Granite 4.2 30B | GPT-5.2 Pro |
| Lifecycle | active | active |
| Released | 2026-08-25 | 2025-12-11 |
| Knowledge cutoff | Unknown | 2025-08-31 |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 131K | 400K |
| Total parameters | 29.3B | Unknown |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Deepinfra (Standard) | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, reasoning, structured_outputs, tools |
14 comparable fields · 10 material differences · Pair passes the primary-source comparison gate
Granite 4.2 30B Capabilities
GPT-5.2 Pro Capabilities
Internal Comparison Graph
Related Comparisons
| A | Pair | B | Context |
|---|---|---|---|
| vs | GPT-6 AstraOpenAI | cross-developer peerstext | |
Claude Fable 5.1Anthropic | vs | cross-developer peerstext | |
Gemini 3.1 ProGoogle DeepMind | vs | cross-developer peerstext | |
DeepSeek-V4-ProDeepSeek | vs | cross-developer peerstext | |
| vs | Grok 4.6xAI | cross-developer peerstext | |
| vs | Qwen3.8-MaxQwen | cross-developer peerstext | |
| vs | Kimi-K3Moonshot AI | cross-developer peerstext | |
MiniMax-M3MiniMax | vs | cross-developer peerstext | |
| vs | GLM-5.3Z.ai | cross-developer peerstext | |
| vs | Hy4 previewTencent | cross-developer peerstext | |
Seed 2.1 ProByteDance Seed | vs | cross-developer peerstext | |
| vs | Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Granite 4.2 30B vs GPT-5.2 Pro FAQs
Is Granite 4.2 30B or GPT-5.2 Pro better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Granite 4.2 30B and GPT-5.2 Pro, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Granite 4.2 30B or GPT-5.2 Pro?+
Granite 4.2 30B is $0.16 and GPT-5.2 Pro is $21.00 per million tokens, so Granite 4.2 30B is cheaper on this metric. Granite 4.2 30B is $0.65 and GPT-5.2 Pro is $168.00 per million tokens, so Granite 4.2 30B is cheaper on this metric.
Which has a larger context window, Granite 4.2 30B or GPT-5.2 Pro?+
GPT-5.2 Pro has the larger sourced context window. Granite 4.2 30B supports 131K and GPT-5.2 Pro supports 400K.
Which performs better in benchmarks, Granite 4.2 30B or GPT-5.2 Pro?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Granite 4.2 30B or GPT-5.2 Pro be self-hosted?+
Granite 4.2 30B is the only model in this pair currently marked as self-hostable. Granite 4.2 30B is open weight; GPT-5.2 Pro is not marked open weight.
Can Granite 4.2 30B and GPT-5.2 Pro understand images?+
Granite 4.2 30B is not documented with image input; GPT-5.2 Pro is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Granite 4.2 30B or GPT-5.2 Pro?+
Neither has a larger sourced maximum output. Granite 4.2 30B is — and GPT-5.2 Pro is 128K.
Do Granite 4.2 30B and GPT-5.2 Pro support reasoning and tool use?+
Granite 4.2 30B: reasoning and tool calling. GPT-5.2 Pro: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Granite 4.2 30B or GPT-5.2 Pro?+
Granite 4.2 30B has 1 sourced provider route; GPT-5.2 Pro has 2, so GPT-5.2 Pro has broader tracked availability.
Which offers better value, Granite 4.2 30B or GPT-5.2 Pro?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.