Last refreshed 2026-10-26. Next refresh: weekly.
Why use Mistral NeMo Instruct (2407) on Vercel AI Gateway?
Vercel AI Gateway offers Mistral NeMo Instruct (2407) with pay-as-you-go pricing at $0.02/1M input tokens. Vercel AI Gateway is a unified AI proxy providing a single OpenAI-compatible API endpoint to 275+ models from 25+ providers including Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, xAI, Alibaba, Amazon, ByteDance, Cohere, MiniMax, MoonshotAI, KwaiPilot, Black Forest Labs, Recraft, Voyage AI, NVIDIA, and more.
Compare Mistral NeMo Instruct (2407) across 12 providers to find the best fit for your use caseInput / 1M
$0.020
Output / 1M
$0.040
Cache
Not sourced
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install openaiAuth
export AI_GATEWAY_API_KEY=...Call
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],Model ID
mistral/mistral-nemoRequest example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],
base_url="https://ai-gateway.vercel.sh/v1"
)
response = client.chat.completions.create(
model="mistral/mistral-nemo",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "mistral/mistral-nemo", not the LLMReference slug "mistral-nemo-instruct".
- creator/model-name e.g. kwaipilot/kat-coder-pro-v2
- The examples expect AI_GATEWAY_API_KEY; rename it only if your application config maps the new variable.
Compare Mistral NeMo Instruct (2407) Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| NVIDIA NIM | — | — |
| Microsoft Foundry | $0.30 | $0.30 |
| DeepInfra | $0.02 | $0.04 |
| Mistral AI Studio | $0.15 | $0.15 |
| OpenRouter | $0.15 | $0.15 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.02 |
| Output tokens | $0.04 |
Capabilities
No model capability flags are currently sourced.
About Mistral NeMo Instruct (2407)
Mistral NeMo Instruct (2407) is MistralAI's Mistral NeMo model. It offers a 128K-token context window and scores 57.1 on GPQA.
Get Started
Model Specs
Released2024-07-18
Parameters12B
Context128K
ArchitectureDecoder Only
Knowledge cutoff2024-04