Embed v3 vs Qwen3 235B Instruct (Cerebras): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Embed v3 (Cohere) 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: Embed v3 at $1.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestEmbed v3 | Cohere | $1.50 | $0.000150 | $1.00 | $0.50 | 87.5% | Alerts coming soon |
Qwen3 235B Instruct (Cerebras) | Cerebras | $12.00 | $0.001200 | $6.00 | $6.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Embed v3 | Qwen3 235B Instruct (Cerebras) | Cheaper |
|---|---|---|---|
| Input (standard) | $0.10/M | $0.60/M | Embed v3 |
| Output | $0.10/M | $1.20/M | Embed v3 |
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 | Embed v3Monthly | Qwen3 235B Instruct (Cerebras)Monthly | Embed v3Per request | Qwen3 235B Instruct (Cerebras)Per request |
|---|---|---|---|---|
| 1K requests/mo | $0.15 | $1.20 | $0.000150 | $0.001200 |
| 10K requests/mo | $1.50 | $12.00 | $0.000150 | $0.001200 |
| 100K requests/mo | $15.00 | $120.00 | $0.000150 | $0.001200 |
| 1M requests/mo | $150.00 | $1,200.00 | $0.000150 | $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 Embed v3
by Cohere
- RAG / Semantic search
Input / 1M tokens
$0.10/M
Output / 1M tokens
$0.10/M
Context window
512
Tier
budget
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 | Embed v3 | Qwen3 235B Instruct (Cerebras) |
|---|---|---|
| Context window | 512 tokens | 128,000 tokens |
| Max output tokens | 1,024 tokens | 32,768 tokens |
| Performance tier | Budget | Premium |
| Vision / image input | No | No |
| Function calling | No | Yes |
| JSON mode | No | Yes |
| Prompt caching | No | No |
| Batch API (50% discount) | No | No |
| Extended reasoning | No | Yes |
| Fine-tuning | No | No |
Embed v3 notes
Embedding model only. Output tokens represent embedding dimensions, not text. Multilingual variant also available.
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 Embed v3 cheaper than Qwen3 235B Instruct (Cerebras)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Embed v3 costs $15.00/month versus $120.00/month for Qwen3 235B Instruct (Cerebras) — a 88% 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, Embed v3 or Qwen3 235B Instruct (Cerebras)?
Qwen3 235B Instruct (Cerebras) has a larger context window at 128,000 tokens, compared to 512 tokens for Embed v3. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Embed v3 and Qwen3 235B Instruct (Cerebras) support the Batch API?
Neither Embed v3 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?
Neither Embed v3 nor Qwen3 235B Instruct (Cerebras) currently supports prompt caching. For prompt-caching capable alternatives, consider Claude models from Anthropic or GPT-4o from OpenAI.
What are the best use cases for Embed v3 vs Qwen3 235B Instruct (Cerebras)?
Both models are well-suited for RAG / Semantic search. Embed v3 is particularly strong for overlapping tasks. Qwen3 235B Instruct (Cerebras) is favored for Code generation, 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 Embed v3 vs Qwen3 235B Instruct (Cerebras)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Embed v3 costs $0.000150 per request and Qwen3 235B Instruct (Cerebras) costs $0.001200 per request. At 100,000 requests/month, that translates to $15.00 and $120.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Embed v3 vs Qwen3 235B Instruct (Cerebras): Summary
When comparing Embed v3 and Qwen3 235B Instruct (Cerebras) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Embed v3 offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $15.00/month, compared to $120.00/month for Qwen3 235B Instruct (Cerebras).
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Embed v3 charges $0.10/M for input tokens and $0.10/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.
Context window capacity differs between the two: Qwen3 235B Instruct (Cerebras) supports up to 128,000 tokens in a single request, versus 512 tokens for Embed v3. 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 Embed v3 or Qwen3 235B Instruct (Cerebras) is recommended.