Pricing, context window, capabilities, and release date — pulled from each provider's public docs. Both are available via the same AIgateway OpenAI-compatible endpoint; flip the model string to switch.
Both models stream in parallel through your own AIgateway key. Tokens, latency, and cost update as they arrive.
| Mistral-7b-Instruct-V0.1-Awq hf/thebloke/mistral-7b-instruct-v0.1-awq | Mistral Small 4 mistral/mistral-small-4-0-26-03 | |
|---|---|---|
| Provider | Hugging Face | Mistral |
| Family | Mistral | Mistral |
| Modality | text | text |
| Context window | 4,096 tok | 131,072 tok |
| Max output | 4,096 tok | 16,384 tok |
| Released | 2023-09-27 | 2026-03-01 |
| Input price | $0.050 /1M | $0.200 /1M |
| Output price | $0.100 /1M | $0.600 /1M |
| Cache read | — | — |
| Tools | — | yes |
| Streaming | yes | yes |
| Vision | — | yes |
| JSON mode | — | yes |
| Reasoning | — | — |
| Prompt caching | — | — |
Mistral 7B Instruct v0.1 AWQ is an efficient, accurate and blazing-fast low-bit weight quantized Mistral variant.
Mistral Small 4 (Mar 2026) — compact frontier-class text model.
# pip install aigateway-py openai
# aigateway-py: sub-accounts, evals, replays, jobs, webhook verify.
# openai SDK: chat/embeddings/images/audio — drop-in compat per our SDK's own guidance.
from openai import OpenAI
client = OpenAI(
base_url="https://api.aigateway.sh/v1",
api_key="sk-aig-...",
)
# Try Mistral-7b-Instruct-V0.1-Awq
client.chat.completions.create(
model="hf/thebloke/mistral-7b-instruct-v0.1-awq",
messages=[{"role":"user","content":"hello"}],
)
# Try Mistral Small 4 — same client, same key
client.chat.completions.create(
model="mistral/mistral-small-4-0-26-03",
messages=[{"role":"user","content":"hello"}],
)