GPT-4.1 nano vs Mistral: Mistral Medium 3.5: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for GPT-4.1 nano (OpenAI) and Mistral: Mistral Medium 3.5 (Mistral AI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified May 6, 2026
Interactive Cost Calculator
Fills in typical token counts for a workload type
Tokens in each prompt sent to the model
Tokens generated in each response
Total API calls per month
Showing costs for 2 models. Cheapest: GPT-4.1 nano at $3.00/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestGPT-4.1 nano | OpenAI | $3.00 | $0.000300 | $1.00 | $2.00 | 94.3% | Alerts coming soon |
Mistral: Mistral Medium 3.5 | Mistral AI | $52.50 | $0.005250 | $15.00 | $37.50 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | GPT-4.1 nano | Mistral: Mistral Medium 3.5 | Cheaper |
|---|---|---|---|
| Input (standard) | $0.10/M | $1.50/M | GPT-4.1 nano |
| Output | $0.40/M | $7.50/M | GPT-4.1 nano |
| Cached input | $0.03/M | N/A | — |
| Batch input | $0.05/M | N/A | — |
| Batch output | $0.20/M | N/A | — |
Prices last verified: 2026-03-08 – 2026-05-06
Cost Breakdown by Usage Volume
Estimated monthly costs at different request volumes, assuming 1,000 input tokens and 500 output tokens per request. Adjust in the calculator above for your specific use case.
| Volume | GPT-4.1 nanoMonthly | Mistral: Mistral Medium 3.5Monthly | GPT-4.1 nanoPer request | Mistral: Mistral Medium 3.5Per request |
|---|---|---|---|---|
| 1K requests/mo | $0.30 | $5.25 | $0.000300 | $0.005250 |
| 10K requests/mo | $3.00 | $52.50 | $0.000300 | $0.005250 |
| 100K requests/mo | $30.00 | $525.00 | $0.000300 | $0.005250 |
| 1M requests/mo | $300.00 | $5,250.00 | $0.000300 | $0.005250 |
Green values indicate the lower-cost option at each volume tier. Cost per request is calculated at 1,000 input + 500 output tokens using standard (non-batch, non-cached) pricing.
Price History
Input price per 1M tokensWhen to Choose GPT-4.1 nano
by OpenAI
- Text classification
- Data extraction
Input / 1M tokens
$0.10/M
Output / 1M tokens
$0.40/M
Context window
1,047,576
Tier
budget
When to Choose Mistral: Mistral Medium 3.5
by Mistral AI
- General chatbot
Input / 1M tokens
$1.50/M
Output / 1M tokens
$7.50/M
Context window
262,144
Tier
mid
Key Differences Beyond Price
Cost is only one factor in choosing an AI model. Context window size, rate limits, supported features, and latency all affect whether a model fits your use case.
| Capability | GPT-4.1 nano | Mistral: Mistral Medium 3.5 |
|---|---|---|
| Context window | 1,047,576 tokens | 262,144 tokens |
| Max output tokens | 32,768 tokens | 4,096 tokens |
| Performance tier | Budget | Mid |
| Vision / image input | Yes | Yes |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | Yes | No |
| Batch API (50% discount) | Yes | No |
| Extended reasoning | No | Yes |
| Fine-tuning | No | No |
| Rate limit (req/min) | 10,000 | Not published |
GPT-4.1 nano notes
Lowest cost OpenAI model. Best for high-volume structured extraction.
Frequently Asked Questions
Is GPT-4.1 nano cheaper than Mistral: Mistral Medium 3.5?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), GPT-4.1 nano costs $30.00/month versus $525.00/month for Mistral: Mistral Medium 3.5 — a 94% saving. Your actual savings will vary based on your token profile; output-heavy workloads amplify differences in output pricing.
Which model has a larger context window, GPT-4.1 nano or Mistral: Mistral Medium 3.5?
GPT-4.1 nano has a larger context window at 1,047,576 tokens, compared to 262,144 tokens for Mistral: Mistral Medium 3.5. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do GPT-4.1 nano and Mistral: Mistral Medium 3.5 support the Batch API?
GPT-4.1 nano supports the Batch API (50% discount for async processing), while Mistral: Mistral Medium 3.5 does not. If your workload tolerates up to 24-hour latency, routing to GPT-4.1 nano with batch pricing could significantly cut costs versus Mistral: Mistral Medium 3.5's standard rate.
Which model offers better prompt caching?
GPT-4.1 nano supports prompt caching at $0.03/M for cached input, while Mistral: Mistral Medium 3.5 does not offer prompt caching. For RAG applications or chatbots with large, repeated context, GPT-4.1 nano's caching capability can substantially reduce effective costs.
What are the best use cases for GPT-4.1 nano vs Mistral: Mistral Medium 3.5?
GPT-4.1 nano is best suited for Text classification, Data extraction, while Mistral: Mistral Medium 3.5 is optimized for General chatbot. Choose based on which use case matches your primary workload — and validate with the cost calculator above to confirm the total monthly spend fits your budget.
What is the cost per request for GPT-4.1 nano vs Mistral: Mistral Medium 3.5?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — GPT-4.1 nano costs $0.000300 per request and Mistral: Mistral Medium 3.5 costs $0.005250 per request. At 100,000 requests/month, that translates to $30.00 and $525.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
GPT-4.1 nano vs Mistral: Mistral Medium 3.5: Summary
When comparing GPT-4.1 nano and Mistral: Mistral Medium 3.5 for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. GPT-4.1 nano offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $30.00/month, compared to $525.00/month for Mistral: Mistral Medium 3.5.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. GPT-4.1 nano charges $0.10/M for input tokens and $0.40/M for output tokens. Mistral: Mistral Medium 3.5 charges $1.50/M input and $7.50/M output. If your workload is output-heavy (more tokens generated than consumed as input), the model with the lower output price compounds cost savings significantly at scale.
Prompt caching is supported by GPT-4.1 nano but not Mistral: Mistral Medium 3.5. For workloads with large, repeated system prompts or document context — such as RAG pipelines or multi-turn conversations with a fixed knowledge base — prompt caching can reduce effective input costs by 60–90%, which may change the cost ranking between these two models at your specific usage pattern.
Context window capacity differs between the two: GPT-4.1 nano supports up to 1,047,576 tokens in a single request, versus 262,144 tokens for Mistral: Mistral Medium 3.5. A larger context window is essential for document summarization, large codebase analysis, and multi-document retrieval-augmented generation (RAG) applications.
Use the interactive calculator at the top of this page to enter your actual token usage and monthly request volume for a precise cost comparison tailored to your workload. Adjust for batch API discounts and prompt caching to find the most cost-effective option for your specific deployment.
Related Comparisons
Explore other model comparisons from the same providers or performance tiers.
Related Provider Pages
View complete pricing tables and model lineups for the providers behind these models.
Relevant Use Cases
See cost recommendations for workloads where GPT-4.1 nano or Mistral: Mistral Medium 3.5 is recommended.