DeepSeek V4 Pro vs Llama 3.1 70B (Bedrock): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for DeepSeek V4 Pro (DeepSeek) and Llama 3.1 70B (Bedrock) (AWS Bedrock). 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
Fills in typical token counts for a workload type
Tokens in each prompt sent to the model
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Total API calls per month
Showing costs for 2 models. Cheapest: DeepSeek V4 Pro at $8.70/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestDeepSeek V4 Pro | DeepSeek | $8.70 | $0.000870 | $4.35 | $4.35 | 73.1% | Alerts coming soon |
Llama 3.1 70B (Bedrock) | AWS Bedrock | $32.30 | $0.003230 | $19.50 | $12.80 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | DeepSeek V4 Pro | Llama 3.1 70B (Bedrock) | Cheaper |
|---|---|---|---|
| Input (standard) | $0.44/M | $1.95/M | DeepSeek V4 Pro |
| Output | $0.87/M | $2.56/M | DeepSeek V4 Pro |
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 | DeepSeek V4 ProMonthly | Llama 3.1 70B (Bedrock)Monthly | DeepSeek V4 ProPer request | Llama 3.1 70B (Bedrock)Per request |
|---|---|---|---|---|
| 1K requests/mo | $0.87 | $3.23 | $0.000870 | $0.003230 |
| 10K requests/mo | $8.70 | $32.30 | $0.000870 | $0.003230 |
| 100K requests/mo | $87.00 | $323.00 | $0.000870 | $0.003230 |
| 1M requests/mo | $870.00 | $3,230.00 | $0.000870 | $0.003230 |
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 DeepSeek V4 Pro
by DeepSeek
- General chatbot
Input / 1M tokens
$0.44/M
Output / 1M tokens
$0.87/M
Context window
1,048,576
Tier
premium
When to Choose Llama 3.1 70B (Bedrock)
by AWS Bedrock
- General chatbot
- Summarization
- Rag Retrieval
Input / 1M tokens
$1.95/M
Output / 1M tokens
$2.56/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 | DeepSeek V4 Pro | Llama 3.1 70B (Bedrock) |
|---|---|---|
| Context window | 1,048,576 tokens | 128,000 tokens |
| Max output tokens | 384,000 tokens | 4,096 tokens |
| Performance tier | Premium | Mid |
| Vision / image input | No | No |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | No | No |
| Batch API (50% discount) | No | Yes |
| Extended reasoning | Yes | No |
| Fine-tuning | No | No |
Llama 3.1 70B (Bedrock) notes
Meta Llama 3.1 70B via AWS Bedrock. Good balance of capability and cost for enterprise workloads requiring open-weight model governance.
Frequently Asked Questions
Is DeepSeek V4 Pro cheaper than Llama 3.1 70B (Bedrock)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), DeepSeek V4 Pro costs $87.00/month versus $323.00/month for Llama 3.1 70B (Bedrock) — a 73% 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, DeepSeek V4 Pro or Llama 3.1 70B (Bedrock)?
DeepSeek V4 Pro has a larger context window at 1,048,576 tokens, compared to 128,000 tokens for Llama 3.1 70B (Bedrock). A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do DeepSeek V4 Pro and Llama 3.1 70B (Bedrock) support the Batch API?
Llama 3.1 70B (Bedrock) supports the Batch API (50% discount for async processing), while DeepSeek V4 Pro does not. If your workload tolerates up to 24-hour latency, routing to Llama 3.1 70B (Bedrock) with batch pricing could significantly cut costs versus DeepSeek V4 Pro's standard rate.
Which model offers better prompt caching?
Neither DeepSeek V4 Pro nor Llama 3.1 70B (Bedrock) 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 DeepSeek V4 Pro vs Llama 3.1 70B (Bedrock)?
Both models are well-suited for General chatbot. DeepSeek V4 Pro is particularly strong for overlapping tasks. Llama 3.1 70B (Bedrock) is favored for Summarization, Rag Retrieval. 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 DeepSeek V4 Pro vs Llama 3.1 70B (Bedrock)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — DeepSeek V4 Pro costs $0.000870 per request and Llama 3.1 70B (Bedrock) costs $0.003230 per request. At 100,000 requests/month, that translates to $87.00 and $323.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
DeepSeek V4 Pro vs Llama 3.1 70B (Bedrock): Summary
When comparing DeepSeek V4 Pro and Llama 3.1 70B (Bedrock) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. DeepSeek V4 Pro offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $87.00/month, compared to $323.00/month for Llama 3.1 70B (Bedrock).
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. DeepSeek V4 Pro charges $0.44/M for input tokens and $0.87/M for output tokens. Llama 3.1 70B (Bedrock) charges $1.95/M input and $2.56/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: DeepSeek V4 Pro supports up to 1,048,576 tokens in a single request, versus 128,000 tokens for Llama 3.1 70B (Bedrock). 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 DeepSeek V4 Pro or Llama 3.1 70B (Bedrock) is recommended.