o3 vs Qwen3 235B Instruct (Cerebras): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for o3 (OpenAI) and Qwen3 235B Instruct (Cerebras) (Cerebras). 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 235B Instruct (Cerebras) at $12.00/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestQwen3 235B Instruct (Cerebras) | Cerebras | $12.00 | $0.001200 | $6.00 | $6.00 | 80.0% | 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 235B Instruct (Cerebras) | Cheaper |
|---|---|---|---|
| Input (standard) | $2.00/M | $0.60/M | Qwen3 235B Instruct (Cerebras) |
| Output | $8.00/M | $1.20/M | Qwen3 235B Instruct (Cerebras) |
| Cached input | $0.50/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 | o3Monthly | Qwen3 235B Instruct (Cerebras)Monthly | o3Per request | Qwen3 235B Instruct (Cerebras)Per request |
|---|---|---|---|---|
| 1K requests/mo | $6.00 | $1.20 | $0.006000 | $0.001200 |
| 10K requests/mo | $60.00 | $12.00 | $0.006000 | $0.001200 |
| 100K requests/mo | $600.00 | $120.00 | $0.006000 | $0.001200 |
| 1M requests/mo | $6,000.00 | $1,200.00 | $0.006000 | $0.001200 |
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 235B Instruct (Cerebras)
by Cerebras
- Code generation
- Document summarization
- RAG / Semantic search
Input / 1M tokens
$0.60/M
Output / 1M tokens
$1.20/M
Context window
128,000
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 | o3 | Qwen3 235B Instruct (Cerebras) |
|---|---|---|
| Context window | 200,000 tokens | 128,000 tokens |
| Max output tokens | 100,000 tokens | 32,768 tokens |
| Performance tier | Reasoning | Premium |
| Vision / image input | Yes | No |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | Yes | No |
| Batch API (50% discount) | No | No |
| Extended reasoning | Yes | Yes |
| 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 235B Instruct (Cerebras) notes
Preview model on Cerebras: ~1,400 tokens/sec. May be discontinued without notice. Hybrid thinking/non-thinking modes supported.
Frequently Asked Questions
Is o3 cheaper than Qwen3 235B Instruct (Cerebras)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Qwen3 235B Instruct (Cerebras) costs $120.00/month versus $600.00/month for o3 — a 80% 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 235B Instruct (Cerebras)?
o3 has a larger context window at 200,000 tokens, compared to 128,000 tokens for Qwen3 235B Instruct (Cerebras). A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do o3 and Qwen3 235B Instruct (Cerebras) support the Batch API?
Neither o3 nor Qwen3 235B Instruct (Cerebras) 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?
o3 supports prompt caching at $0.50/M for cached input, while Qwen3 235B Instruct (Cerebras) does not offer prompt caching. For RAG applications or chatbots with large, repeated context, o3's caching capability can substantially reduce effective costs.
What are the best use cases for o3 vs Qwen3 235B Instruct (Cerebras)?
Both models are well-suited for Code generation, Document summarization. o3 is particularly strong for overlapping tasks. Qwen3 235B Instruct (Cerebras) is favored for RAG / Semantic search. 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 235B Instruct (Cerebras)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — o3 costs $0.006000 per request and Qwen3 235B Instruct (Cerebras) costs $0.001200 per request. At 100,000 requests/month, that translates to $600.00 and $120.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
o3 vs Qwen3 235B Instruct (Cerebras): Summary
When comparing o3 and Qwen3 235B Instruct (Cerebras) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Qwen3 235B Instruct (Cerebras) offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $120.00/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 235B Instruct (Cerebras) charges $0.60/M input and $1.20/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 o3 but not Qwen3 235B Instruct (Cerebras). 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 supports up to 200,000 tokens in a single request, versus 128,000 tokens for Qwen3 235B Instruct (Cerebras). 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
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