Mistral Small 4 vs Qwen3 VL 30B (Fireworks): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Mistral Small 4 (Mistral AI) and Qwen3 VL 30B (Fireworks) (Fireworks AI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified Apr 30, 2026
Interactive Cost Calculator
Fills in typical token counts for a workload type
Tokens in each prompt sent to the model
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Total API calls per month
Showing costs for 2 models. Cheapest: Mistral Small 4 at $4.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestMistral Small 4 | Mistral AI | $4.50 | $0.000450 | $1.50 | $3.00 | — | Alerts coming soon |
Qwen3 VL 30B (Fireworks) | Fireworks AI | $4.50 | $0.000450 | $1.50 | $3.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Mistral Small 4 | Qwen3 VL 30B (Fireworks) | Cheaper |
|---|---|---|---|
| Input (standard) | $0.15/M | $0.15/M | — |
| Output | $0.60/M | $0.60/M | — |
| Cached input | N/A | $0.08/M | — |
| Batch input | N/A | $0.08/M | — |
| Batch output | N/A | $0.30/M | — |
Prices last verified: 2026-03-10 – 2026-04-30
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 | Mistral Small 4Monthly | Qwen3 VL 30B (Fireworks)Monthly | Mistral Small 4Per request | Qwen3 VL 30B (Fireworks)Per request |
|---|---|---|---|---|
| 1K requests/mo | $0.45 | $0.45 | $0.000450 | $0.000450 |
| 10K requests/mo | $4.50 | $4.50 | $0.000450 | $0.000450 |
| 100K requests/mo | $45.00 | $45.00 | $0.000450 | $0.000450 |
| 1M requests/mo | $450.00 | $450.00 | $0.000450 | $0.000450 |
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 Mistral Small 4
by Mistral AI
- General chatbot
Input / 1M tokens
$0.15/M
Output / 1M tokens
$0.60/M
Context window
262,144
Tier
budget
When to Choose Qwen3 VL 30B (Fireworks)
by Fireworks AI
- Document summarization
- General chatbot
Input / 1M tokens
$0.15/M
Output / 1M tokens
$0.60/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 | Mistral Small 4 | Qwen3 VL 30B (Fireworks) |
|---|---|---|
| Context window | 262,144 tokens | 262,144 tokens |
| Max output tokens | 4,096 tokens | 8,192 tokens |
| Performance tier | Budget | Mid |
| Vision / image input | No | Yes |
| Function calling | No | Yes |
| JSON mode | No | Yes |
| Prompt caching | No | Yes |
| Batch API (50% discount) | No | Yes |
| Extended reasoning | No | No |
| Fine-tuning | No | No |
Qwen3 VL 30B (Fireworks) notes
Fireworks serverless pricing. Vision/multimodal capable. Cached input 50% discount.
Frequently Asked Questions
Is Mistral Small 4 cheaper than Qwen3 VL 30B (Fireworks)?
Mistral Small 4 and Qwen3 VL 30B (Fireworks) cost the same at standard usage (1,000 input + 500 output tokens, 100K requests/month): $45.00/month each. For different token ratios, use the calculator above.
Which model has a larger context window, Mistral Small 4 or Qwen3 VL 30B (Fireworks)?
Both Mistral Small 4 and Qwen3 VL 30B (Fireworks) have the same context window: 262,144 tokens.
Do Mistral Small 4 and Qwen3 VL 30B (Fireworks) support the Batch API?
Qwen3 VL 30B (Fireworks) supports the Batch API (50% discount for async processing), while Mistral Small 4 does not. If your workload tolerates up to 24-hour latency, routing to Qwen3 VL 30B (Fireworks) with batch pricing could significantly cut costs versus Mistral Small 4's standard rate.
Which model offers better prompt caching?
Qwen3 VL 30B (Fireworks) supports prompt caching at $0.08/M for cached input, while Mistral Small 4 does not offer prompt caching. For RAG applications or chatbots with large, repeated context, Qwen3 VL 30B (Fireworks)'s caching capability can substantially reduce effective costs.
What are the best use cases for Mistral Small 4 vs Qwen3 VL 30B (Fireworks)?
Both models are well-suited for General chatbot. Mistral Small 4 is particularly strong for overlapping tasks. Qwen3 VL 30B (Fireworks) is favored for Document summarization. At the same quality level, the lower-cost model is usually preferable; use this page's calculator to compare total monthly spend at your volume.
What is the cost per request for Mistral Small 4 vs Qwen3 VL 30B (Fireworks)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Mistral Small 4 costs $0.000450 per request and Qwen3 VL 30B (Fireworks) costs $0.000450 per request. At 100,000 requests/month, that translates to $45.00 and $45.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Mistral Small 4 vs Qwen3 VL 30B (Fireworks): Summary
When comparing Mistral Small 4 and Qwen3 VL 30B (Fireworks) 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 $45.00/month.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Mistral Small 4 charges $0.15/M for input tokens and $0.60/M for output tokens. Qwen3 VL 30B (Fireworks) charges $0.15/M input and $0.60/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 Qwen3 VL 30B (Fireworks) but not Mistral Small 4. 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: Both models support 262,144 tokens per request. 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 Mistral Small 4 or Qwen3 VL 30B (Fireworks) is recommended.