Llama 3.1 8B (SambaNova) vs Mistral Small 3.2: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Llama 3.1 8B (SambaNova) (SambaNova) and Mistral Small 3.2 (Mistral AI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified Apr 30, 2026
Interactive Cost Calculator
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Showing costs for 2 models. Cheapest: Llama 3.1 8B (SambaNova) at $2.00/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestLlama 3.1 8B (SambaNova) | SambaNova | $2.00 | $0.000200 | $1.00 | $1.00 | 20.0% | Alerts coming soon |
Mistral Small 3.2 | Mistral AI | $2.50 | $0.000250 | $1.00 | $1.50 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Llama 3.1 8B (SambaNova) | Mistral Small 3.2 | Cheaper |
|---|---|---|---|
| Input (standard) | $0.10/M | $0.10/M | — |
| Output | $0.20/M | $0.30/M | Llama 3.1 8B (SambaNova) |
Prices last verified: 2026-03-11 – 2026-04-30
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 | Llama 3.1 8B (SambaNova)Monthly | Mistral Small 3.2Monthly | Llama 3.1 8B (SambaNova)Per request | Mistral Small 3.2Per request |
|---|---|---|---|---|
| 1K requests/mo | $0.20 | $0.25 | $0.000200 | $0.000250 |
| 10K requests/mo | $2.00 | $2.50 | $0.000200 | $0.000250 |
| 100K requests/mo | $20.00 | $25.00 | $0.000200 | $0.000250 |
| 1M requests/mo | $200.00 | $250.00 | $0.000200 | $0.000250 |
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 Llama 3.1 8B (SambaNova)
by SambaNova
- Text classification
- Data extraction
- Customer support
Input / 1M tokens
$0.10/M
Output / 1M tokens
$0.20/M
Context window
128,000
Tier
budget
When to Choose Mistral Small 3.2
by Mistral AI
- Text classification
- Data extraction
- Customer support
Input / 1M tokens
$0.10/M
Output / 1M tokens
$0.30/M
Context window
32,768
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 | Llama 3.1 8B (SambaNova) | Mistral Small 3.2 |
|---|---|---|
| Context window | 128,000 tokens | 32,768 tokens |
| Max output tokens | 8,192 tokens | 4,096 tokens |
| Performance tier | Budget | 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 | Yes |
Llama 3.1 8B (SambaNova) notes
Llama 3.1 8B on SambaNova. Best-in-class throughput for budget workloads. Ideal for high-volume, low-latency inference tasks.
Mistral Small 3.2 notes
Supports fine-tuning. Good for specialized classification tasks.
Frequently Asked Questions
Is Llama 3.1 8B (SambaNova) cheaper than Mistral Small 3.2?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Llama 3.1 8B (SambaNova) costs $20.00/month versus $25.00/month for Mistral Small 3.2 — a 20% 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, Llama 3.1 8B (SambaNova) or Mistral Small 3.2?
Llama 3.1 8B (SambaNova) has a larger context window at 128,000 tokens, compared to 32,768 tokens for Mistral Small 3.2. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Llama 3.1 8B (SambaNova) and Mistral Small 3.2 support the Batch API?
Neither Llama 3.1 8B (SambaNova) nor Mistral Small 3.2 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 Llama 3.1 8B (SambaNova) nor Mistral Small 3.2 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 Llama 3.1 8B (SambaNova) vs Mistral Small 3.2?
Both models are well-suited for Text classification, Data extraction, Customer support. Llama 3.1 8B (SambaNova) is particularly strong for overlapping tasks. Mistral Small 3.2 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 Llama 3.1 8B (SambaNova) vs Mistral Small 3.2?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Llama 3.1 8B (SambaNova) costs $0.000200 per request and Mistral Small 3.2 costs $0.000250 per request. At 100,000 requests/month, that translates to $20.00 and $25.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Llama 3.1 8B (SambaNova) vs Mistral Small 3.2: Summary
When comparing Llama 3.1 8B (SambaNova) and Mistral Small 3.2 for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Llama 3.1 8B (SambaNova) offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $20.00/month, compared to $25.00/month for Mistral Small 3.2.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Llama 3.1 8B (SambaNova) charges $0.10/M for input tokens and $0.20/M for output tokens. Mistral Small 3.2 charges $0.10/M input and $0.30/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: Llama 3.1 8B (SambaNova) supports up to 128,000 tokens in a single request, versus 32,768 tokens for Mistral Small 3.2. 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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