GPT OSS 20B (Fireworks) vs Llama 3.1 8B (Groq): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for GPT OSS 20B (Fireworks) (Fireworks AI) and Llama 3.1 8B (Groq) (Groq). 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 (Groq) at $0.90/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestLlama 3.1 8B (Groq) | Groq | $0.90 | $0.000090 | $0.50 | $0.40 | 59.1% | Alerts coming soon |
GPT OSS 20B (Fireworks) | Fireworks AI | $2.20 | $0.000220 | $0.70 | $1.50 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | GPT OSS 20B (Fireworks) | Llama 3.1 8B (Groq) | Cheaper |
|---|---|---|---|
| Input (standard) | $0.07/M | $0.05/M | Llama 3.1 8B (Groq) |
| Output | $0.30/M | $0.08/M | Llama 3.1 8B (Groq) |
| Cached input | $0.04/M | N/A | — |
| Batch input | $0.04/M | N/A | — |
| Batch output | $0.15/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 20B (Fireworks)Monthly | Llama 3.1 8B (Groq)Monthly | GPT OSS 20B (Fireworks)Per request | Llama 3.1 8B (Groq)Per request |
|---|---|---|---|---|
| 1K requests/mo | $0.22 | $0.09 | $0.000220 | $0.000090 |
| 10K requests/mo | $2.20 | $0.90 | $0.000220 | $0.000090 |
| 100K requests/mo | $22.00 | $9.00 | $0.000220 | $0.000090 |
| 1M requests/mo | $220.00 | $90.00 | $0.000220 | $0.000090 |
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 20B (Fireworks)
by Fireworks AI
- Customer support
- Text classification
- General chatbot
Input / 1M tokens
$0.07/M
Output / 1M tokens
$0.30/M
Context window
131,072
Tier
budget
When to Choose Llama 3.1 8B (Groq)
by Groq
- Text classification
- Customer support
Input / 1M tokens
$0.05/M
Output / 1M tokens
$0.08/M
Context window
131,072
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 20B (Fireworks) | Llama 3.1 8B (Groq) |
|---|---|---|
| Context window | 131,072 tokens | 131,072 tokens |
| Max output tokens | 16,384 tokens | 8,000 tokens |
| Performance tier | Budget | Budget |
| Vision / image input | No | No |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | Yes | No |
| Batch API (50% discount) | Yes | No |
| Extended reasoning | No | No |
| Fine-tuning | No | No |
| Rate limit (req/min) | Not published | 30 |
GPT OSS 20B (Fireworks) notes
Fireworks serverless pricing. Cached input 50% discount. Batch at 50% of serverless.
Llama 3.1 8B (Groq) notes
Extremely low cost. Best for latency-sensitive high-volume simple tasks.
Frequently Asked Questions
Is GPT OSS 20B (Fireworks) cheaper than Llama 3.1 8B (Groq)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Llama 3.1 8B (Groq) costs $9.00/month versus $22.00/month for GPT OSS 20B (Fireworks) — a 59% 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 20B (Fireworks) or Llama 3.1 8B (Groq)?
Both GPT OSS 20B (Fireworks) and Llama 3.1 8B (Groq) have the same context window: 131,072 tokens.
Do GPT OSS 20B (Fireworks) and Llama 3.1 8B (Groq) support the Batch API?
GPT OSS 20B (Fireworks) supports the Batch API (50% discount for async processing), while Llama 3.1 8B (Groq) does not. If your workload tolerates up to 24-hour latency, routing to GPT OSS 20B (Fireworks) with batch pricing could significantly cut costs versus Llama 3.1 8B (Groq)'s standard rate.
Which model offers better prompt caching?
GPT OSS 20B (Fireworks) supports prompt caching at $0.04/M for cached input, while Llama 3.1 8B (Groq) does not offer prompt caching. For RAG applications or chatbots with large, repeated context, GPT OSS 20B (Fireworks)'s caching capability can substantially reduce effective costs.
What are the best use cases for GPT OSS 20B (Fireworks) vs Llama 3.1 8B (Groq)?
Both models are well-suited for Customer support, Text classification. GPT OSS 20B (Fireworks) is particularly strong for General chatbot. Llama 3.1 8B (Groq) is favored for similar workflows. 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 20B (Fireworks) vs Llama 3.1 8B (Groq)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — GPT OSS 20B (Fireworks) costs $0.000220 per request and Llama 3.1 8B (Groq) costs $0.000090 per request. At 100,000 requests/month, that translates to $22.00 and $9.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
GPT OSS 20B (Fireworks) vs Llama 3.1 8B (Groq): Summary
When comparing GPT OSS 20B (Fireworks) and Llama 3.1 8B (Groq) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Llama 3.1 8B (Groq) offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $9.00/month, compared to $22.00/month for GPT OSS 20B (Fireworks).
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. GPT OSS 20B (Fireworks) charges $0.07/M for input tokens and $0.30/M for output tokens. Llama 3.1 8B (Groq) charges $0.05/M input and $0.08/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 GPT OSS 20B (Fireworks) but not Llama 3.1 8B (Groq). 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: Both models support 131,072 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 20B (Fireworks) or Llama 3.1 8B (Groq) is recommended.