Kimi K2 Instruct (Fireworks) vs Llama 3.1 70B (SambaNova): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Kimi K2 Instruct (Fireworks) (Fireworks AI) and Llama 3.1 70B (SambaNova) (SambaNova). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified Mar 11, 2026
Interactive Cost Calculator
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Showing costs for 2 models. Cheapest: Llama 3.1 70B (SambaNova) at $12.00/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestLlama 3.1 70B (SambaNova) | SambaNova | $12.00 | $0.001200 | $6.00 | $6.00 | 35.1% | Alerts coming soon |
Kimi K2 Instruct (Fireworks) | Fireworks AI | $18.50 | $0.001850 | $6.00 | $12.50 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Kimi K2 Instruct (Fireworks) | Llama 3.1 70B (SambaNova) | Cheaper |
|---|---|---|---|
| Input (standard) | $0.60/M | $0.60/M | — |
| Output | $2.50/M | $1.20/M | Llama 3.1 70B (SambaNova) |
| Cached input | $0.30/M | N/A | — |
| Batch input | $0.30/M | N/A | — |
| Batch output | $1.25/M | N/A | — |
Prices last verified: 2026-03-10 – 2026-03-11
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 | Kimi K2 Instruct (Fireworks)Monthly | Llama 3.1 70B (SambaNova)Monthly | Kimi K2 Instruct (Fireworks)Per request | Llama 3.1 70B (SambaNova)Per request |
|---|---|---|---|---|
| 1K requests/mo | $1.85 | $1.20 | $0.001850 | $0.001200 |
| 10K requests/mo | $18.50 | $12.00 | $0.001850 | $0.001200 |
| 100K requests/mo | $185.00 | $120.00 | $0.001850 | $0.001200 |
| 1M requests/mo | $1,850.00 | $1,200.00 | $0.001850 | $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 Kimi K2 Instruct (Fireworks)
by Fireworks AI
- Code generation
- Document summarization
- RAG / Semantic search
Input / 1M tokens
$0.60/M
Output / 1M tokens
$2.50/M
Context window
131,072
Tier
mid
When to Choose Llama 3.1 70B (SambaNova)
by SambaNova
- General chatbot
- Content Creation
- Summarization
Input / 1M tokens
$0.60/M
Output / 1M tokens
$1.20/M
Context window
128,000
Tier
mid
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 | Kimi K2 Instruct (Fireworks) | Llama 3.1 70B (SambaNova) |
|---|---|---|
| Context window | 131,072 tokens | 128,000 tokens |
| Max output tokens | 16,384 tokens | 8,192 tokens |
| Performance tier | Mid | Mid |
| 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 |
Kimi K2 Instruct (Fireworks) notes
Fireworks serverless pricing. Cached input 50% discount. Batch at 50% of serverless.
Llama 3.1 70B (SambaNova) notes
Llama 3.1 70B on SambaNova. Excellent price-to-performance ratio for mid-tier workloads with fast inference speeds.
Frequently Asked Questions
Is Kimi K2 Instruct (Fireworks) cheaper than Llama 3.1 70B (SambaNova)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Llama 3.1 70B (SambaNova) costs $120.00/month versus $185.00/month for Kimi K2 Instruct (Fireworks) — a 35% 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, Kimi K2 Instruct (Fireworks) or Llama 3.1 70B (SambaNova)?
Kimi K2 Instruct (Fireworks) has a larger context window at 131,072 tokens, compared to 128,000 tokens for Llama 3.1 70B (SambaNova). A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Kimi K2 Instruct (Fireworks) and Llama 3.1 70B (SambaNova) support the Batch API?
Kimi K2 Instruct (Fireworks) supports the Batch API (50% discount for async processing), while Llama 3.1 70B (SambaNova) does not. If your workload tolerates up to 24-hour latency, routing to Kimi K2 Instruct (Fireworks) with batch pricing could significantly cut costs versus Llama 3.1 70B (SambaNova)'s standard rate.
Which model offers better prompt caching?
Kimi K2 Instruct (Fireworks) supports prompt caching at $0.30/M for cached input, while Llama 3.1 70B (SambaNova) does not offer prompt caching. For RAG applications or chatbots with large, repeated context, Kimi K2 Instruct (Fireworks)'s caching capability can substantially reduce effective costs.
What are the best use cases for Kimi K2 Instruct (Fireworks) vs Llama 3.1 70B (SambaNova)?
Kimi K2 Instruct (Fireworks) is best suited for Code generation, Document summarization, RAG / Semantic search, while Llama 3.1 70B (SambaNova) is optimized for General chatbot, Content Creation, Summarization. Choose based on which use case matches your primary workload — and validate with the cost calculator above to confirm the total monthly spend fits your budget.
What is the cost per request for Kimi K2 Instruct (Fireworks) vs Llama 3.1 70B (SambaNova)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Kimi K2 Instruct (Fireworks) costs $0.001850 per request and Llama 3.1 70B (SambaNova) costs $0.001200 per request. At 100,000 requests/month, that translates to $185.00 and $120.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Kimi K2 Instruct (Fireworks) vs Llama 3.1 70B (SambaNova): Summary
When comparing Kimi K2 Instruct (Fireworks) and Llama 3.1 70B (SambaNova) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Llama 3.1 70B (SambaNova) 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 $185.00/month for Kimi K2 Instruct (Fireworks).
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Kimi K2 Instruct (Fireworks) charges $0.60/M for input tokens and $2.50/M for output tokens. Llama 3.1 70B (SambaNova) 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 Kimi K2 Instruct (Fireworks) but not Llama 3.1 70B (SambaNova). 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: Kimi K2 Instruct (Fireworks) supports up to 131,072 tokens in a single request, versus 128,000 tokens for Llama 3.1 70B (SambaNova). 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 Kimi K2 Instruct (Fireworks) or Llama 3.1 70B (SambaNova) is recommended.