Mistral Nemo Instruct 2407
mistral/nemo-instruct-2407By Mistral · family: mistral-nemo · released 2024-07-18 · knowledge: 2024-05
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capabilities
Model fit scores
0–100 · higher is betterThese scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.
Coding69
- Tool calling40/40
- Structured output20/20
- Reasoning0/10
- Context window (100K → 1M)2/20
- Provider availability7/10
Agents82
- Tool calling35/35
- Structured output25/25
- Reasoning0/15
- Output token limit15/15
- Provider availability7/10
JSON / structured output100
- Structured output / JSON mode50/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume20/20
Cost efficiency98
- Headline price (log-scaled)93/95
- Has prompt-cache pricing5/5
Long context46
- Context window (100K → 2M)36/90
- Has published price for full window10/10
Production-readiness91
- Number of independent providers35/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers6/10
- Official model (not derivative)15/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $0.12 < $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $0.23 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | $0.06 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $0.19 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $0.26 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Pricing detail
Recommended pricing from pioneer · mistralai/Mistral-Nemo-Instruct-2407
Available on 7 providers
| Provider | Provider model id | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|---|
| Meganova meganova | mistralai/Mistral-Nemo-Instruct-2407 | $0.020 | $0.040 | 131K | 2024-07-18 |
| Cortecs cortecs | mistral-nemo-instruct-2407 | $0.145 | $0.145 | 128K | 2024-08-07 |
| NanoGPT nano-gpt | mistralai/Mistral-Nemo-Instruct-2407 | $0.100 | $0.121 | 16K | 2024-01-01 |
| OVHcloud AI Endpoints ovhcloud | mistral-nemo-instruct-2407 | $0.140 | $0.140 | 66K | 2024-11-20 |
| DigitalOcean digitalocean | mistral-nemo-instruct-2407 | $0.300 | $0.300 | 128K | 2024-07-18 |
| IO.NET io-net | mistralai/Mistral-Nemo-Instruct-2407 | $0.020 | $0.040 | 128K | 2024-07-01 |
| Pioneer pioneer | mistralai/Mistral-Nemo-Instruct-2407 | $0.020 | $0.030 | 131K | 2024-07-01 |
Data inconsistencies across providers
- context_window varies: 128000, 131072, 16384, 65536
- release_date varies (span 324d): 2024-01-01, 2024-07-01, 2024-07-18, 2024-08-07, 2024-11-20
Different providers report different values for this model. Quick facts above use the representative provider; consult the table for per-provider truth.
Frequently asked questions
How much does Mistral Nemo Instruct 2407 cost?
Mistral Nemo Instruct 2407 costs $0.020 per 1M input tokens and $0.030 per 1M output tokens, sourced from pioneer. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Mistral Nemo Instruct 2407?
Mistral Nemo Instruct 2407 has a context window of 131K tokens, with a max output of 66K tokens per reply. This is the total combined size of prompt + completion.
Does Mistral Nemo Instruct 2407 support tool calling?
Yes. Mistral Nemo Instruct 2407 supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Does Mistral Nemo Instruct 2407 support structured output / JSON mode?
Yes. Mistral Nemo Instruct 2407 supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Can Mistral Nemo Instruct 2407 accept image input?
No. Mistral Nemo Instruct 2407 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Mistral Nemo Instruct 2407 open-weight?
Yes. Mistral Nemo Instruct 2407's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.
What are the best alternatives to Mistral Nemo Instruct 2407?
If Mistral Nemo Instruct 2407 doesn't fit, consider Mistral Large 3, Mistral Small 3.2 24B Instruct, Mistral Medium 3.5. Each one targets the same use case — see the Related links below for direct head-to-head pages.
Where does this data come from?
All numbers are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More Mistral models
- Mistral Large 3$0.50 in / $1.50 out
- Mistral Small 3.2 24B Instruct$0.10 in / $0.31 out
- Mistral Medium 3.5$1.67 in / $5.57 out
- Mistral Nemo$0.15 in / $0.15 out
- Mistral-7B-Instruct-v0.3$0.11 in / $0.11 out
Capability lists this model is in
Last updated:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.