GPT OSS 120B (Cerebras) vs Llama 3.1 8B (Cerebras): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for GPT OSS 120B (Cerebras) (Cerebras) and Llama 3.1 8B (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: Llama 3.1 8B (Cerebras) at $1.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestLlama 3.1 8B (Cerebras) | Cerebras | $1.50 | $0.000150 | $1.00 | $0.50 | 79.3% | Alerts coming soon |
GPT OSS 120B (Cerebras) | Cerebras | $7.25 | $0.000725 | $3.50 | $3.75 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | GPT OSS 120B (Cerebras) | Llama 3.1 8B (Cerebras) | Cheaper |
|---|---|---|---|
| Input (standard) | $0.35/M | $0.10/M | Llama 3.1 8B (Cerebras) |
| Output | $0.75/M | $0.10/M | Llama 3.1 8B (Cerebras) |
Prices last verified: 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 (Cerebras)Monthly | Llama 3.1 8B (Cerebras)Monthly | GPT OSS 120B (Cerebras)Per request | Llama 3.1 8B (Cerebras)Per request |
|---|---|---|---|---|
| 1K requests/mo | $0.72 | $0.15 | $0.000725 | $0.000150 |
| 10K requests/mo | $7.25 | $1.50 | $0.000725 | $0.000150 |
| 100K requests/mo | $72.50 | $15.00 | $0.000725 | $0.000150 |
| 1M requests/mo | $725.00 | $150.00 | $0.000725 | $0.000150 |
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 (Cerebras)
by Cerebras
- Code generation
- Document summarization
- General chatbot
Input / 1M tokens
$0.35/M
Output / 1M tokens
$0.75/M
Context window
128,000
Tier
mid
When to Choose Llama 3.1 8B (Cerebras)
by Cerebras
- Customer support
- Text classification
- General chatbot
Input / 1M tokens
$0.10/M
Output / 1M tokens
$0.10/M
Context window
128,000
Tier
budget
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 (Cerebras) | Llama 3.1 8B (Cerebras) |
|---|---|---|
| Context window | 128,000 tokens | 128,000 tokens |
| Max output tokens | 16,384 tokens | 8,192 tokens |
| Performance tier | Mid | Budget |
| Vision / image input | No | No |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | No | No |
| Batch API (50% discount) | No | No |
| Extended reasoning | No | No |
| Fine-tuning | No | No |
GPT OSS 120B (Cerebras) notes
Cerebras wafer-scale inference: ~3,000 tokens/sec. Best for latency-critical production workloads requiring a large model.
Llama 3.1 8B (Cerebras) notes
Cerebras wafer-scale inference: ~2,200 tokens/sec — roughly 20x faster than GPU providers. Ideal for latency-sensitive real-time applications.
Frequently Asked Questions
Is GPT OSS 120B (Cerebras) cheaper than Llama 3.1 8B (Cerebras)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Llama 3.1 8B (Cerebras) costs $15.00/month versus $72.50/month for GPT OSS 120B (Cerebras) — a 79% 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 (Cerebras) or Llama 3.1 8B (Cerebras)?
Both GPT OSS 120B (Cerebras) and Llama 3.1 8B (Cerebras) have the same context window: 128,000 tokens.
Do GPT OSS 120B (Cerebras) and Llama 3.1 8B (Cerebras) support the Batch API?
Neither GPT OSS 120B (Cerebras) nor Llama 3.1 8B (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 GPT OSS 120B (Cerebras) nor Llama 3.1 8B (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 GPT OSS 120B (Cerebras) vs Llama 3.1 8B (Cerebras)?
Both models are well-suited for General chatbot. GPT OSS 120B (Cerebras) is particularly strong for Code generation, Document summarization. Llama 3.1 8B (Cerebras) is favored for Customer support, Text classification. 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 (Cerebras) vs Llama 3.1 8B (Cerebras)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — GPT OSS 120B (Cerebras) costs $0.000725 per request and Llama 3.1 8B (Cerebras) costs $0.000150 per request. At 100,000 requests/month, that translates to $72.50 and $15.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
GPT OSS 120B (Cerebras) vs Llama 3.1 8B (Cerebras): Summary
When comparing GPT OSS 120B (Cerebras) and Llama 3.1 8B (Cerebras) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Llama 3.1 8B (Cerebras) 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 $72.50/month for GPT OSS 120B (Cerebras).
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. GPT OSS 120B (Cerebras) charges $0.35/M for input tokens and $0.75/M for output tokens. Llama 3.1 8B (Cerebras) charges $0.10/M input and $0.10/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: Both models support 128,000 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 GPT OSS 120B (Cerebras) or Llama 3.1 8B (Cerebras) is recommended.