Open Mistral Nemo
Mistral AI chatOpen Mistral Nemo is a Mistral AI chat model.It supports a 128,000-token context windowwith up to 128,000 output tokens.Input is priced at $0.300/M tokens and output at $0.300/M tokens. Route Open Mistral Nemo via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Open Mistral Nemo spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $0.3000/M input · $0.3000/M output. Provider pricing changes. Production costs vary with retries, streaming overhead, and tool-call rounds.
Want this for free? Cache + route via Agent Command Center — first 100K requests and 100K cache hits free every month.
Pricing
Per-token rates, expressed in USD per 1M tokens. Verified May 12, 2026.
| Input | $0.300/M | |
| Output | $0.300/M |
Limits
- Context window
- 128,000 tokens
- Max input
- 128,000 tokens
- Max output
- 128,000 tokens
- Modalities
- text
Capabilities
- Function calling — not advertised
- Parallel tool calls — not advertised
- Vision input — not advertised
- Audio input — not advertised
- Audio output — not advertised
- PDF input — not advertised
- Streaming ✓ supported
- Structured output ✓ supported
- Prompt caching — not advertised
- Reasoning — not advertised
Where it's strong
Watch out for
- !agentic workflows — no advertised function-calling; use a tool-capable model and route via Agent Command Center for fallback
Benchmarks pending
We haven't logged public benchmark scores for Open Mistral Nemo yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Open Mistral Nemo via Agent Command Center
One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.
agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.# Open Mistral Nemo via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC
client = AgentCC(
api_key=os.environ["AGENTCC_API_KEY"], # from app.futureagi.com → Settings → API Keys
base_url="https://gateway.futureagi.com/v1",
)
resp = client.chat.completions.create(
model="mistral/open-mistral-nemo",
messages=[{"role": "user", "content": "Hello, Open Mistral Nemo!"}],
)
print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")
# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
model="mistral/open-mistral-nemo",
messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost: ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache: ", raw.headers.get("x-agentcc-cache"))AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗Compare with similar models
Open Mistral Nemo doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark.
FAQ
How much does Open Mistral Nemo cost?
Input is priced at $0.300 per 1M tokens and output at $0.300 per 1M tokens (Mistral AI, last verified May 12, 2026).
What is the context window of Open Mistral Nemo?
Open Mistral Nemo supports a 128,000-token context window with up to 128,000 output tokens.
Does Open Mistral Nemo support function calling?
Open Mistral Nemo does not currently advertise function-calling support. For agentic workloads, prefer a tool-calling-capable model and route via Agent Command Center for fallback.
Is Open Mistral Nemo good for production?
Open Mistral Nemo is best evaluated against your own production traces. Pipe traffic through Agent Command Center to compare it head-to-head against alternatives in shadow mode.
How can I route to Open Mistral Nemo with fallback?
Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.
Useful links for Open Mistral Nemo
Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.
Third-party evals — verify the marketing.
Cross-check our number against the rest of the ecosystem.