Mixtral-8x7B-Instruct-v0.1
ovhcloud · chat model
Input
$0.6300 / 1M tokens
Output
$0.6300 / 1M tokens
Cached input
N/A
Context
32.0K
Pricing
| Item | Raw value (per token) | Normalized |
|---|---|---|
| Input | 6.3e-7 | $0.6300 / 1M tokens |
| Output | 6.3e-7 | $0.6300 / 1M tokens |
| Embedding | 6.3e-7 | $0.6300 / 1M tokens |
Token limits
Context window
32.0K
Max input tokens
32.0K
Max output tokens
32.0K
Max tokens
32.0K
Capabilities
| Capability | Supported |
|---|---|
| Vision | No |
| Function calling | No |
| Parallel function calling | No |
| Tool choice | No |
| Prompt caching | No |
| Reasoning | No |
| Response schema | Yes |
| System messages | No |
| Audio input | No |
| Audio output | No |
| Web search | No |
| PDF input | No |
| Video input | No |
Similar models
Models with comparable pricing in the same mode (chat).
| Model | Provider | Input | Output | Context | Coding | Features |
|---|---|---|---|---|---|---|
| wizardlm-2-8x22b | novita | $0.6200 / 1M tokens | $0.6200 / 1M tokens | 8.0K | N/A | |
| llama3.3-70b-instruct | gradient_ai | $0.6500 / 1M tokens | $0.6500 / 1M tokens | 2.0K | N/A | |
| mixtral-8x22b-instruct | OpenRouter | $0.6500 / 1M tokens | $0.6500 / 1M tokens | 65.5K | N/A | |
| llama3.1-70b | cerebras | $0.6000 / 1M tokens | $0.6000 / 1M tokens | 128.0K | N/A | Tools |
| Llama-3.1-Nemotron-70B-Instruct | deepinfra | $0.6000 / 1M tokens | $0.6000 / 1M tokens | 131.1K | N/A | Tools |
| meta-llama-3.1-70b-instruct | friendliai | $0.6000 / 1M tokens | $0.6000 / 1M tokens | 8.2K | N/A | Tools |
Sources
| Pricing source | LiteLLM model cost map |
| Synced at | 2026-05-27 |
| Manual review | Not reviewed |
Raw LiteLLM fields
{
"input_cost_per_token": 6.3e-7,
"litellm_provider": "ovhcloud",
"max_input_tokens": 32000,
"max_output_tokens": 32000,
"max_tokens": 32000,
"mode": "chat",
"output_cost_per_token": 6.3e-7,
"source": "https://endpoints.ai.cloud.ovh.net/models/mixtral-8x7b-instruct-v0-1",
"supports_function_calling": false,
"supports_response_schema": true,
"supports_tool_choice": false
}