o3 vs Qwen3 VL 30B (Fireworks): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for o3 (OpenAI) 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 Mar 10, 2026
Interactive Cost Calculator
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Showing costs for 2 models. Cheapest: Qwen3 VL 30B (Fireworks) at $4.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestQwen3 VL 30B (Fireworks) | Fireworks AI | $4.50 | $0.000450 | $1.50 | $3.00 | 92.5% | Alerts coming soon |
o3 | OpenAI | $60.00 | $0.006000 | $20.00 | $40.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | o3 | Qwen3 VL 30B (Fireworks) | Cheaper |
|---|---|---|---|
| Input (standard) | $2.00/M | $0.15/M | Qwen3 VL 30B (Fireworks) |
| Output | $8.00/M | $0.60/M | Qwen3 VL 30B (Fireworks) |
| Cached input | $0.50/M | $0.08/M | Qwen3 VL 30B (Fireworks) |
| Batch input | N/A | $0.08/M | — |
| Batch output | N/A | $0.30/M | — |
Prices last verified: 2026-03-06 – 2026-03-10
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 | o3Monthly | Qwen3 VL 30B (Fireworks)Monthly | o3Per request | Qwen3 VL 30B (Fireworks)Per request |
|---|---|---|---|---|
| 1K requests/mo | $6.00 | $0.45 | $0.006000 | $0.000450 |
| 10K requests/mo | $60.00 | $4.50 | $0.006000 | $0.000450 |
| 100K requests/mo | $600.00 | $45.00 | $0.006000 | $0.000450 |
| 1M requests/mo | $6,000.00 | $450.00 | $0.006000 | $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 o3
by OpenAI
- Code generation
- Document summarization
Input / 1M tokens
$2.00/M
Output / 1M tokens
$8.00/M
Context window
200,000
Tier
reasoning
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 | o3 | Qwen3 VL 30B (Fireworks) |
|---|---|---|
| Context window | 200,000 tokens | 262,144 tokens |
| Max output tokens | 100,000 tokens | 8,192 tokens |
| Performance tier | Reasoning | Mid |
| Vision / image input | Yes | Yes |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | Yes | Yes |
| Batch API (50% discount) | No | Yes |
| Extended reasoning | Yes | No |
| Fine-tuning | No | No |
| Rate limit (req/min) | 1,000 | Not published |
o3 notes
State-of-the-art reasoning performance. Costs reflect internal thinking tokens. Price reduced significantly from launch.
Qwen3 VL 30B (Fireworks) notes
Fireworks serverless pricing. Vision/multimodal capable. Cached input 50% discount.
Frequently Asked Questions
Is o3 cheaper than Qwen3 VL 30B (Fireworks)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Qwen3 VL 30B (Fireworks) costs $45.00/month versus $600.00/month for o3 — a 93% 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, o3 or Qwen3 VL 30B (Fireworks)?
Qwen3 VL 30B (Fireworks) has a larger context window at 262,144 tokens, compared to 200,000 tokens for o3. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do o3 and Qwen3 VL 30B (Fireworks) support the Batch API?
Qwen3 VL 30B (Fireworks) supports the Batch API (50% discount for async processing), while o3 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 o3's standard rate.
Which model offers better prompt caching?
Both o3 and Qwen3 VL 30B (Fireworks) support prompt caching. o3 caches repeated input at $0.50/M (vs $2.00/M standard), while Qwen3 VL 30B (Fireworks) caches at $0.08/M (vs $0.15/M standard). For workloads with large, repeated system prompts or document context, caching can reduce effective input costs by 60–90%.
What are the best use cases for o3 vs Qwen3 VL 30B (Fireworks)?
Both models are well-suited for Document summarization. o3 is particularly strong for Code generation. Qwen3 VL 30B (Fireworks) is favored for General chatbot. 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 o3 vs Qwen3 VL 30B (Fireworks)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — o3 costs $0.006000 per request and Qwen3 VL 30B (Fireworks) costs $0.000450 per request. At 100,000 requests/month, that translates to $600.00 and $45.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
o3 vs Qwen3 VL 30B (Fireworks): Summary
When comparing o3 and Qwen3 VL 30B (Fireworks) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Qwen3 VL 30B (Fireworks) offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $45.00/month, compared to $600.00/month for o3.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. o3 charges $2.00/M for input tokens and $8.00/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 both models. 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: Qwen3 VL 30B (Fireworks) supports up to 262,144 tokens in a single request, versus 200,000 tokens for o3. 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 o3 or Qwen3 VL 30B (Fireworks) is recommended.