GPT OSS 120B (Fireworks) vs o3-mini: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for GPT OSS 120B (Fireworks) (Fireworks AI) and o3-mini (OpenAI). 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: GPT OSS 120B (Fireworks) at $4.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestGPT OSS 120B (Fireworks) | Fireworks AI | $4.50 | $0.000450 | $1.50 | $3.00 | 86.4% | Alerts coming soon |
o3-mini | OpenAI | $33.00 | $0.003300 | $11.00 | $22.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | GPT OSS 120B (Fireworks) | o3-mini | Cheaper |
|---|---|---|---|
| Input (standard) | $0.15/M | $1.10/M | GPT OSS 120B (Fireworks) |
| Output | $0.60/M | $4.40/M | GPT OSS 120B (Fireworks) |
| Cached input | $0.08/M | $0.55/M | GPT OSS 120B (Fireworks) |
| Batch input | $0.08/M | N/A | — |
| Batch output | $0.30/M | N/A | — |
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 | GPT OSS 120B (Fireworks)Monthly | o3-miniMonthly | GPT OSS 120B (Fireworks)Per request | o3-miniPer request |
|---|---|---|---|---|
| 1K requests/mo | $0.45 | $3.30 | $0.000450 | $0.003300 |
| 10K requests/mo | $4.50 | $33.00 | $0.000450 | $0.003300 |
| 100K requests/mo | $45.00 | $330.00 | $0.000450 | $0.003300 |
| 1M requests/mo | $450.00 | $3,300.00 | $0.000450 | $0.003300 |
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 OSS 120B (Fireworks)
by Fireworks AI
- Code generation
- Document summarization
- RAG / Semantic search
Input / 1M tokens
$0.15/M
Output / 1M tokens
$0.60/M
Context window
131,072
Tier
mid
When to Choose o3-mini
by OpenAI
- Code generation
- Data extraction
Input / 1M tokens
$1.10/M
Output / 1M tokens
$4.40/M
Context window
200,000
Tier
reasoning
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 OSS 120B (Fireworks) | o3-mini |
|---|---|---|
| Context window | 131,072 tokens | 200,000 tokens |
| Max output tokens | 16,384 tokens | 100,000 tokens |
| Performance tier | Mid | Reasoning |
| Vision / image input | No | No |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | Yes | Yes |
| Batch API (50% discount) | Yes | No |
| Extended reasoning | No | Yes |
| Fine-tuning | No | No |
| Rate limit (req/min) | Not published | 1,000 |
GPT OSS 120B (Fireworks) notes
Fireworks serverless pricing. Cached input 50% discount. Batch at 50% of serverless.
o3-mini notes
Configurable reasoning effort (low/medium/high). No vision support.
Frequently Asked Questions
Is GPT OSS 120B (Fireworks) cheaper than o3-mini?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), GPT OSS 120B (Fireworks) costs $45.00/month versus $330.00/month for o3-mini — a 86% 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 OSS 120B (Fireworks) or o3-mini?
o3-mini has a larger context window at 200,000 tokens, compared to 131,072 tokens for GPT OSS 120B (Fireworks). A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do GPT OSS 120B (Fireworks) and o3-mini support the Batch API?
GPT OSS 120B (Fireworks) supports the Batch API (50% discount for async processing), while o3-mini does not. If your workload tolerates up to 24-hour latency, routing to GPT OSS 120B (Fireworks) with batch pricing could significantly cut costs versus o3-mini's standard rate.
Which model offers better prompt caching?
Both GPT OSS 120B (Fireworks) and o3-mini support prompt caching. GPT OSS 120B (Fireworks) caches repeated input at $0.08/M (vs $0.15/M standard), while o3-mini caches at $0.55/M (vs $1.10/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 GPT OSS 120B (Fireworks) vs o3-mini?
Both models are well-suited for Code generation. GPT OSS 120B (Fireworks) is particularly strong for Document summarization, RAG / Semantic search. o3-mini is favored for Data extraction. 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 GPT OSS 120B (Fireworks) vs o3-mini?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — GPT OSS 120B (Fireworks) costs $0.000450 per request and o3-mini costs $0.003300 per request. At 100,000 requests/month, that translates to $45.00 and $330.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
GPT OSS 120B (Fireworks) vs o3-mini: Summary
When comparing GPT OSS 120B (Fireworks) and o3-mini for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. GPT OSS 120B (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 $330.00/month for o3-mini.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. GPT OSS 120B (Fireworks) charges $0.15/M for input tokens and $0.60/M for output tokens. o3-mini charges $1.10/M input and $4.40/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: o3-mini supports up to 200,000 tokens in a single request, versus 131,072 tokens for GPT OSS 120B (Fireworks). 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 OSS 120B (Fireworks) or o3-mini is recommended.