Gemma 4 12B IT vs Llama 4 Maverick 17B
Gemma 4 12B IT (2026) and Llama 4 Maverick 17B (2025) are frontier reasoning models from Google DeepMind and AI at Meta. Gemma 4 12B IT ships a 256k-token context window, while Llama 4 Maverick 17B ships a 128k-token context window. On Google-Proof Q&A, Gemma 4 12B IT leads by 11.7 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Gemma 4 12B IT is safer overall; choose Llama 4 Maverick 17B when coding workflow support matters.
Decision scorecard
Local evidence first| Signal | Gemma 4 12B IT | Llama 4 Maverick 17B |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | multimodal apps and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 256k | 128k |
| Cheapest output | - | $0.60/1M tokens |
| Provider routes | 2 tracked | 2 tracked |
| Shared benchmarks | Google-Proof Q&A leader | 1 rows |
Decision tradeoffs
- Gemma 4 12B IT leads the largest shared benchmark signal on Google-Proof Q&A by 11.7 points.
- Gemma 4 12B IT has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemma 4 12B IT uniquely exposes Vision, Reasoning, and Function calling in local model data.
- Local decision data tags Gemma 4 12B IT for Coding, RAG, and Agents.
- Llama 4 Maverick 17B uniquely exposes Code execution in local model data.
- Local decision data tags Llama 4 Maverick 17B for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemma 4 12B IT
Unavailable
No complete token price in local provider data
Llama 4 Maverick 17B
$270
Cheapest tracked route/tier: OpenRouter
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Gemma 4 12B IT and Llama 4 Maverick 17B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision, Reasoning, and Function calling before moving production traffic.
- Llama 4 Maverick 17B adds Code execution in local capability data.
- No overlapping tracked provider route is sourced for Llama 4 Maverick 17B and Gemma 4 12B IT; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Code execution before moving production traffic.
- Gemma 4 12B IT adds Vision, Reasoning, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-06-03 | 2025-10-01 |
| Context window | 256k | 128k |
| Parameters | 11.9B | 17 |
| Architecture | encoder free unified multimodal | - |
| License | Apache 2.0 | Open Source |
| Knowledge cutoff | 2025-01 | 2024-08 |
Pricing and availability
| Pricing attribute | Gemma 4 12B IT | Llama 4 Maverick 17B |
|---|---|---|
| Input price | - | $0.15/1M tokens |
| Output price | - | $0.60/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 4 12B IT | Llama 4 Maverick 17B |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | No | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Gemma 4 12B IT | Llama 4 Maverick 17B |
|---|---|---|
| Google-Proof Q&A | 78.8 | 67.1 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Gemma 4 12B IT at 78.8 and Llama 4 Maverick 17B at 67.1, with Gemma 4 12B IT ahead by 11.7 points. The largest visible gap is 11.7 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: Gemma 4 12B IT, reasoning mode: Gemma 4 12B IT, function calling: Gemma 4 12B IT, tool use: Gemma 4 12B IT, and code execution: Llama 4 Maverick 17B. Both models share multimodal input and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
Pricing coverage is uneven: Gemma 4 12B IT has no token price sourced yet and Llama 4 Maverick 17B has $0.15/1M input tokens. Provider availability is 2 tracked routes versus 2. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Gemma 4 12B IT when reasoning depth and larger context windows are central to the workload. Choose Llama 4 Maverick 17B when coding workflow support are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Gemma 4 12B IT or Llama 4 Maverick 17B?
Gemma 4 12B IT supports 256k tokens, while Llama 4 Maverick 17B supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Gemma 4 12B IT or Llama 4 Maverick 17B open source?
Gemma 4 12B IT is listed under Apache 2.0. Llama 4 Maverick 17B is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Gemma 4 12B IT or Llama 4 Maverick 17B?
Gemma 4 12B IT has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Gemma 4 12B IT or Llama 4 Maverick 17B?
Both Gemma 4 12B IT and Llama 4 Maverick 17B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for reasoning mode, Gemma 4 12B IT or Llama 4 Maverick 17B?
Gemma 4 12B IT has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemma 4 12B IT and Llama 4 Maverick 17B?
Gemma 4 12B IT is available on Hugging Face Inference Endpoints and Kaggle Models. Llama 4 Maverick 17B is available on AWS Bedrock and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-03. Data sourced from public model cards and provider documentation.