Gemini 3 Pro vs Llama 3.1 405B Instruct
Gemini 3 Pro (2025) and Llama 3.1 405B Instruct (2024) are compact production models from Google DeepMind and AI at Meta. Gemini 3 Pro ships a 1M-token context window, while Llama 3.1 405B Instruct ships a 128K-token context window. On pricing, Gemini 3 Pro costs $1.25/1M input tokens versus $2.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Gemini 3 Pro is ~92% cheaper at $1.25/1M; pay for Llama 3.1 405B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | Gemini 3 Pro | Llama 3.1 405B Instruct |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | RAG, Long context, and Classification |
| Context window | 1M | 128K |
| Cheapest output | $5/1M tokens | $2.4/1M tokens |
| Provider routes | 2 tracked | 11 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemini 3 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemini 3 Pro uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Gemini 3 Pro for Coding, RAG, and Agents.
- Llama 3.1 405B Instruct has the lower cheapest tracked output price at $2.4/1M tokens.
- Llama 3.1 405B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 3.1 405B Instruct uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 3.1 405B Instruct for RAG, Long context, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Gemini 3 Pro
$2,250
Cheapest tracked route: GCP Vertex AI
Llama 3.1 405B Instruct
$2,520
Cheapest tracked route: AWS Bedrock
Estimated monthly gap: $270. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
- Llama 3.1 405B Instruct is $2.6/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
- Llama 3.1 405B Instruct adds Structured outputs in local capability data.
- Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
- Gemini 3 Pro is $2.6/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Structured outputs before moving production traffic.
- Gemini 3 Pro adds Vision, Multimodal, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-11 | 2024-07-23 |
| Context window | 1M | 128K |
| Parameters | — | 405B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | 2025-01 | - |
Pricing and availability
| Pricing attribute | Gemini 3 Pro | Llama 3.1 405B Instruct |
|---|---|---|
| Input price | $1.25/1M tokens | $2.4/1M tokens |
| Output price | $5/1M tokens | $2.4/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 3 Pro | Llama 3.1 405B Instruct |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | No | Yes |
| Code execution | Yes | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Gemini 3 Pro, multimodal input: Gemini 3 Pro, function calling: Gemini 3 Pro, tool use: Gemini 3 Pro, structured outputs: Llama 3.1 405B Instruct, and code execution: Gemini 3 Pro. Both models share the core language-model surface, 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.
For cost, Gemini 3 Pro lists $1.25/1M input and $5/1M output tokens, while Llama 3.1 405B Instruct lists $2.4/1M input and $2.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemini 3 Pro lower by about $0.02 per million blended tokens. Availability is 2 providers versus 11, so concentration risk also matters.
Choose Gemini 3 Pro when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose Llama 3.1 405B Instruct when provider fit and broader provider choice 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, Gemini 3 Pro or Llama 3.1 405B Instruct?
Gemini 3 Pro supports 1M tokens, while Llama 3.1 405B Instruct supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemini 3 Pro or Llama 3.1 405B Instruct?
Gemini 3 Pro is cheaper on tracked token pricing. Gemini 3 Pro costs $1.25/1M input and $5/1M output tokens. Llama 3.1 405B Instruct costs $2.4/1M input and $2.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 3 Pro or Llama 3.1 405B Instruct open source?
Gemini 3 Pro is listed under Proprietary. Llama 3.1 405B Instruct 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, Gemini 3 Pro or Llama 3.1 405B Instruct?
Gemini 3 Pro 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, Gemini 3 Pro or Llama 3.1 405B Instruct?
Gemini 3 Pro has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemini 3 Pro and Llama 3.1 405B Instruct?
Gemini 3 Pro is available on Replicate API and GCP Vertex AI. Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.