Gemini 3.1 Flash vs Llama 3.1 405B
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Gemini 3.1 Flash and Llama 3.1 405B.
Gemini 3.1 Flash
Gemini 3.1 Flash is Google's high-speed, cost-efficient multimodal model in the 3.1 generation, purpose-built for high-volume content synthesis, classification, and intelligent routing at scale. Featuring a 1-million-token context window, it can process large batches of documents, customer data, or multimedia content in a single inference pass, dramatically reducing pipeline complexity. At just $0.25/MTok for input, it is one of the most affordable routes to Google-caliber multimodal AI, making it an ideal backbone for production pipelines, data enrichment workflows, and high-frequency API integrations.
Llama 3.1 405B
Llama 3.1 405B is Meta's largest open-weight language model and one of the most capable openly available models in the world. With 405 billion parameters, it achieves performance competitive with GPT-4 and Claude Opus across benchmarks spanning general knowledge, mathematics, coding, and multilingual tasks. Llama 3.1 405B is released under Meta's custom commercial license, supporting broad use cases including deployment via major cloud providers (AWS, GCP, Azure) and self-hosted inference with multi-GPU configurations.
Technical Specifications
| Specification | Gemini 3.1 Flash | Llama 3.1 405B |
|---|---|---|
| Provider | Meta | |
| Context Window | 1,000,000 tokens | 131,072 tokens |
| Agent Suitability | 86/100 | 90/100 |
| Time to First Token (TTFT) | 150 ms | 550 ms |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-20 | 2024-07-23 |
API Pricing Comparison
Input Price per Million Tokens
Gemini 3.1 Flash
$0.25
Llama 3.1 405B
$0.80
Output Price per Million Tokens
Gemini 3.1 Flash
$1.50
Llama 3.1 405B
$0.80
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Gemini 3.1 Flash Quirks & Gotchas
- ▸Most cost-effective Google model — ideal for high-volume pipelines
- ▸Context caching available via Vertex AI for repeated document processing
Llama 3.1 405B Quirks & Gotchas
- ▸Massive model — requires 8× A100 80GB for FP16 inference
- ▸Available via Together AI, Fireworks, and Bedrock as managed API