GPT-5 mini vs Mistral Large 3: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for GPT-5 mini (OpenAI) and Mistral Large 3 (Mistral AI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified Mar 8, 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-5 mini at $12.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestGPT-5 mini | OpenAI | $12.50 | $0.001250 | $2.50 | $10.00 | — | Alerts coming soon |
Mistral Large 3 | Mistral AI | $12.50 | $0.001250 | $5.00 | $7.50 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | GPT-5 mini | Mistral Large 3 | Cheaper |
|---|---|---|---|
| Input (standard) | $0.25/M | $0.50/M | GPT-5 mini |
| Output | $2.00/M | $1.50/M | Mistral Large 3 |
| Cached input | $0.03/M | N/A | — |
Prices last verified: 2026-03-08
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-5 miniMonthly | Mistral Large 3Monthly | GPT-5 miniPer request | Mistral Large 3Per request |
|---|---|---|---|---|
| 1K requests/mo | $1.25 | $1.25 | $0.001250 | $0.001250 |
| 10K requests/mo | $12.50 | $12.50 | $0.001250 | $0.001250 |
| 100K requests/mo | $125.00 | $125.00 | $0.001250 | $0.001250 |
| 1M requests/mo | $1,250.00 | $1,250.00 | $0.001250 | $0.001250 |
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-5 mini
by OpenAI
- Customer support
- General chatbot
- Data extraction
Input / 1M tokens
$0.25/M
Output / 1M tokens
$2.00/M
Context window
400,000
Tier
mid
When to Choose Mistral Large 3
by Mistral AI
- Code generation
- Content & copywriting
- RAG / Semantic search
Input / 1M tokens
$0.50/M
Output / 1M tokens
$1.50/M
Context window
262,144
Tier
premium
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-5 mini | Mistral Large 3 |
|---|---|---|
| Context window | 400,000 tokens | 262,144 tokens |
| Max output tokens | 128,000 tokens | 8,192 tokens |
| Performance tier | Mid | Premium |
| Vision / image input | Yes | Yes |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | Yes | No |
| Batch API (50% discount) | No | No |
| Extended reasoning | No | No |
| Fine-tuning | No | No |
| Rate limit (req/min) | 10,000 | Not published |
GPT-5 mini notes
1M context window at mid-tier pricing. Good balance of cost and capability.
Mistral Large 3 notes
Major price reduction from original Mistral Large ($2/$6 -> $0.50/$1.50). Supports 80+ languages.
Frequently Asked Questions
Is GPT-5 mini cheaper than Mistral Large 3?
GPT-5 mini and Mistral Large 3 cost the same at standard usage (1,000 input + 500 output tokens, 100K requests/month): $125.00/month each. For different token ratios, use the calculator above.
Which model has a larger context window, GPT-5 mini or Mistral Large 3?
GPT-5 mini has a larger context window at 400,000 tokens, compared to 262,144 tokens for Mistral Large 3. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do GPT-5 mini and Mistral Large 3 support the Batch API?
Neither GPT-5 mini nor Mistral Large 3 currently supports a batch API with discounted pricing. For batch-eligible alternatives, consider models from OpenAI, Anthropic, or Google that include batch API support.
Which model offers better prompt caching?
GPT-5 mini supports prompt caching at $0.03/M for cached input, while Mistral Large 3 does not offer prompt caching. For RAG applications or chatbots with large, repeated context, GPT-5 mini's caching capability can substantially reduce effective costs.
What are the best use cases for GPT-5 mini vs Mistral Large 3?
GPT-5 mini is best suited for Customer support, General chatbot, Data extraction, while Mistral Large 3 is optimized for Code generation, Content & copywriting, RAG / Semantic search. 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-5 mini vs Mistral Large 3?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — GPT-5 mini costs $0.001250 per request and Mistral Large 3 costs $0.001250 per request. At 100,000 requests/month, that translates to $125.00 and $125.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
GPT-5 mini vs Mistral Large 3: Summary
When comparing GPT-5 mini and Mistral Large 3 for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Both models cost the same at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $125.00/month.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. GPT-5 mini charges $0.25/M for input tokens and $2.00/M for output tokens. Mistral Large 3 charges $0.50/M input and $1.50/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-5 mini but not Mistral Large 3. 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-5 mini supports up to 400,000 tokens in a single request, versus 262,144 tokens for Mistral Large 3. 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.
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Relevant Use Cases
See cost recommendations for workloads where GPT-5 mini or Mistral Large 3 is recommended.