Text model
mistralai/Mixtral-8x7B-Instruct-v0.1 pricing
DeepInfra charges $0.40 per million input tokens and $0.40 per million output tokens for mistralai/Mixtral-8x7B-Instruct-v0.1. Below: every rate that applies, what common workloads cost, and cheaper options.
- Input
- $0.40/ 1M
- Output
- $0.40/ 1M
- Context
- 32.8Ktokens
All rates
| Tier | Input | Output | Cache read | Cache write |
|---|---|---|---|---|
| Standard | $0.40 | $0.40 | — | — |
USD per million tokens. Long-context tiers apply when the whole prompt, cached tokens included, passes the threshold.
Work it out
What common workloads cost
| Workload | Per call | Cost per call | Calls a month | Per month |
|---|---|---|---|---|
| Chat reply | 1,500 input and 400 output tokens | $0.00076 | 100,000 | $76.00 |
| RAG answer, cached context | 2,000 fresh + 4,000 cached input, 500 output | $0.0026 | 100,000 | $260.00 |
| Agent step | 4,000 fresh + 8,000 cached input, 800 output | $0.00512 | 250,000 | $1,280.00 |
| Batch summary | 3,000 input and 300 output tokens via the Batch API | — | 1,000,000 | — |
Planning a mix of models? Simulate a workload with mistralai/Mixtral-8x7B-Instruct-v0.1, alongside anything else you run.
Cheaper options
Current models that cost at least 15% less for a typical chat reply. Cheaper isn't always equivalent: test quality on your own prompts, then use veqen diff to see the impact at your volume.
| Model | Chat reply | Saving |
|---|---|---|
| deepinfra/meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8 | $0.00062 | 18% |
| deepinfra/Qwen/Qwen3.5-35B-A3B | $0.00061 | 20% |
| novita/qwen/qwen3-235b-a22b-fp8 | $0.00062 | 18% |
| azure-ai/Llama-4-Scout-17B-16E-Instruct | $0.000612 | 19% |
Price history
No price changes since Veqen started tracking this model.
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Last verified with price book 2026-10-22. Sources: DeepInfra pricing and LiteLLM's MIT-licensed price file. Track every call to this model, per customer or project: install the SDK.