Last refreshed 2026-05-05. Next refresh: weekly.
Why use Mistral 7B v0.1 on Fireworks AI?
Fireworks AI offers Mistral 7B v0.1 with pay-as-you-go pricing at $0.20/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Compare Mistral 7B v0.1 across 16 providers to find the best fit for your use caseSetup recipe
Python + curlpip install openaiexport FIREWORKS_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],mistral-7b-v0.1Request example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="mistral-7b-v0.1",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
- The examples expect FIREWORKS_API_KEY; rename it only if your application config maps the new variable.
Compare Mistral 7B v0.1 Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| GCP Vertex AI | $0.08 | $0.24 |
| OctoAI API (Deprecated) | — | — |
| DeepInfra | $0.05 | $0.15 |
| Mistral AI Studio | $0.25 | $0.25 |
| Baseten API | — | — |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
No model capability flags are currently sourced.
About Mistral 7B v0.1
Mistral 7B v0.1 is an advanced open-source large language model built by Mistral AI, consisting of 7 billion parameters. It's designed to deliver high performance and efficiency, outperforming many similar-sized models in various benchmarks. The model employs a transformer architecture with innovative features like Sliding Window Attention, Grouped-Query Attention, and a Byte-fallback BPE tokenizer, enhancing speed, reducing computational costs, and improving robustness. Capable of generating human-like text, following instructions effectively, and excelling in areas such as reasoning and mathematics, Mistral 7B v0.1 does have limitations, such as a lack of built-in moderation and a potential for hallucinations.