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Llama 3.1 70B (SambaNova) vs Llama 4 Maverick (Fireworks): API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for Llama 3.1 70B (SambaNova) (SambaNova) and Llama 4 Maverick (Fireworks) (Fireworks AI). 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

SambaNovaLlama 3.1 70B (SambaNova)Fireworks AILlama 4 Maverick (Fireworks)

Fills in typical token counts for a workload type

Tokens in each prompt sent to the model

Tokens generated in each response

Total API calls per month

Showing costs for 2 models. Cheapest: Llama 4 Maverick (Fireworks) at $7.50/month.

Cheapest: Llama 4 Maverick (Fireworks) at $7.50/mo — save 37.5% vs Llama 3.1 70B (SambaNova)
Alert
BestLlama 4 Maverick (Fireworks)
Fireworks AI$7.50$0.000750$5.00$2.5037.5%Alerts coming soon
Llama 3.1 70B (SambaNova)
SambaNova$12.00$0.001200$6.00$6.00Alerts 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 TypeLlama 3.1 70B (SambaNova)Llama 4 Maverick (Fireworks)Cheaper
Input (standard)$0.60/M$0.50/MLlama 4 Maverick (Fireworks)
Output$1.20/M$0.50/MLlama 4 Maverick (Fireworks)
Cached inputN/A$0.25/M
Batch inputN/A$0.25/M
Batch outputN/A$0.25/M

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.

VolumeLlama 3.1 70B (SambaNova)MonthlyLlama 4 Maverick (Fireworks)MonthlyLlama 3.1 70B (SambaNova)Per requestLlama 4 Maverick (Fireworks)Per request
1K requests/mo$1.20$0.75$0.001200$0.000750
10K requests/mo$12.00$7.50$0.001200$0.000750
100K requests/mo$120.00$75.00$0.001200$0.000750
1M requests/mo$1,200.00$750.00$0.001200$0.000750

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 tokens

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

When to Choose Llama 4 Maverick (Fireworks)

by Fireworks AI

  • Code generation
  • Document summarization
  • General chatbot

Input / 1M tokens

$0.50/M

Output / 1M tokens

$0.50/M

Context window

131,072

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.

CapabilityLlama 3.1 70B (SambaNova)Llama 4 Maverick (Fireworks)
Context window128,000 tokens131,072 tokens
Max output tokens8,192 tokens16,384 tokens
Performance tierMidMid
Vision / image inputNoYes
Function callingYesYes
JSON modeYesYes
Prompt cachingNoYes
Batch API (50% discount)NoYes
Extended reasoningNoNo
Fine-tuningNoNo

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.

Llama 4 Maverick (Fireworks) notes

Fireworks serverless pricing. Cached input 50% discount. Batch inference at 50% of serverless rates.

Frequently Asked Questions

Is Llama 3.1 70B (SambaNova) cheaper than Llama 4 Maverick (Fireworks)?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Llama 4 Maverick (Fireworks) costs $75.00/month versus $120.00/month for Llama 3.1 70B (SambaNova) — a 38% 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 70B (SambaNova) or Llama 4 Maverick (Fireworks)?

Llama 4 Maverick (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 Llama 3.1 70B (SambaNova) and Llama 4 Maverick (Fireworks) support the Batch API?

Llama 4 Maverick (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 Llama 4 Maverick (Fireworks) with batch pricing could significantly cut costs versus Llama 3.1 70B (SambaNova)'s standard rate.

Which model offers better prompt caching?

Llama 4 Maverick (Fireworks) supports prompt caching at $0.25/M for cached input, while Llama 3.1 70B (SambaNova) does not offer prompt caching. For RAG applications or chatbots with large, repeated context, Llama 4 Maverick (Fireworks)'s caching capability can substantially reduce effective costs.

What are the best use cases for Llama 3.1 70B (SambaNova) vs Llama 4 Maverick (Fireworks)?

Both models are well-suited for General chatbot. Llama 3.1 70B (SambaNova) is particularly strong for Content Creation, Summarization. Llama 4 Maverick (Fireworks) 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 Llama 3.1 70B (SambaNova) vs Llama 4 Maverick (Fireworks)?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Llama 3.1 70B (SambaNova) costs $0.001200 per request and Llama 4 Maverick (Fireworks) costs $0.000750 per request. At 100,000 requests/month, that translates to $120.00 and $75.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

Llama 3.1 70B (SambaNova) vs Llama 4 Maverick (Fireworks): Summary

When comparing Llama 3.1 70B (SambaNova) and Llama 4 Maverick (Fireworks) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Llama 4 Maverick (Fireworks) offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $75.00/month, compared to $120.00/month for Llama 3.1 70B (SambaNova).

Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Llama 3.1 70B (SambaNova) charges $0.60/M for input tokens and $1.20/M for output tokens. Llama 4 Maverick (Fireworks) charges $0.50/M input and $0.50/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 Llama 4 Maverick (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: Llama 4 Maverick (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.

Explore other model comparisons from the same providers or performance tiers.

Related Provider Pages

View complete pricing tables and model lineups for the providers behind these models.

Relevant Use Cases

See cost recommendations for workloads where Llama 3.1 70B (SambaNova) or Llama 4 Maverick (Fireworks) is recommended.