Last refreshed 2026-06-01. Next refresh: weekly.
Why use Mistral 7B Instruct v0.2 on Fireworks AI?
Fireworks AI offers Mistral 7B Instruct v0.2 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 Instruct v0.2 across 8 providers to find the best fit for your use caseInput / 1M
$0.20
Output / 1M
$0.20
Cache
Not sourced
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install openaiAuth
export FIREWORKS_API_KEY=...Call
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],Model ID
accounts/fireworks/models/mistral-7b-instruct-v0p2Request 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="accounts/fireworks/models/mistral-7b-instruct-v0p2",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "accounts/fireworks/models/mistral-7b-instruct-v0p2", not the LLMReference slug "mistral-7b-instruct-v0.2".
- 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 Instruct v0.2 Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Cloudflare Workers AI | — | — |
| OctoML (Deprecated) | $0.15 | $0.20 |
| DeepInfra | $0.05 | $0.15 |
| Fireworks AI | $0.20 | $0.20 |
| NVIDIA NIM | — | — |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
No model capability flags are currently sourced.
About Mistral 7B Instruct v0.2
Instruction-tuned 7B Mistral variant optimized for conversational AI and task completion with efficient inference.
Get Started
Model Specs
Released2023-12-11
Parameters7B
Context32k
ArchitectureDecoder Only
Knowledge cutoff2023-12