DeepSeek V3.2 (Bedrock) vs Llama 3.1 70B (Bedrock): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for DeepSeek V3.2 (Bedrock) (AWS Bedrock) 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 Mar 11, 2026
Interactive Cost Calculator
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Showing costs for 2 models. Cheapest: DeepSeek V3.2 (Bedrock) at $15.45/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestDeepSeek V3.2 (Bedrock) | AWS Bedrock | $15.45 | $0.001545 | $6.20 | $9.25 | 52.2% | 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 V3.2 (Bedrock) | Llama 3.1 70B (Bedrock) | Cheaper |
|---|---|---|---|
| Input (standard) | $0.62/M | $1.95/M | DeepSeek V3.2 (Bedrock) |
| Output | $1.85/M | $2.56/M | DeepSeek V3.2 (Bedrock) |
Prices last verified: 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 | DeepSeek V3.2 (Bedrock)Monthly | Llama 3.1 70B (Bedrock)Monthly | DeepSeek V3.2 (Bedrock)Per request | Llama 3.1 70B (Bedrock)Per request |
|---|---|---|---|---|
| 1K requests/mo | $1.54 | $3.23 | $0.001545 | $0.003230 |
| 10K requests/mo | $15.45 | $32.30 | $0.001545 | $0.003230 |
| 100K requests/mo | $154.50 | $323.00 | $0.001545 | $0.003230 |
| 1M requests/mo | $1,545.00 | $3,230.00 | $0.001545 | $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 V3.2 (Bedrock)
by AWS Bedrock
- Code generation
- Summarization
- General chatbot
Input / 1M tokens
$0.62/M
Output / 1M tokens
$1.85/M
Context window
128,000
Tier
mid
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 V3.2 (Bedrock) | Llama 3.1 70B (Bedrock) |
|---|---|---|
| Context window | 128,000 tokens | 128,000 tokens |
| Max output tokens | 8,192 tokens | 4,096 tokens |
| Performance tier | Mid | 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 | No | No |
| Fine-tuning | No | No |
DeepSeek V3.2 (Bedrock) notes
DeepSeek V3.2 via AWS Bedrock. Excellent cost/performance ratio for coding and reasoning tasks, with AWS compliance and security guarantees.
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 V3.2 (Bedrock) cheaper than Llama 3.1 70B (Bedrock)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), DeepSeek V3.2 (Bedrock) costs $154.50/month versus $323.00/month for Llama 3.1 70B (Bedrock) — a 52% 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 V3.2 (Bedrock) or Llama 3.1 70B (Bedrock)?
Both DeepSeek V3.2 (Bedrock) and Llama 3.1 70B (Bedrock) have the same context window: 128,000 tokens.
Do DeepSeek V3.2 (Bedrock) 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 V3.2 (Bedrock) 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 V3.2 (Bedrock)'s standard rate.
Which model offers better prompt caching?
Neither DeepSeek V3.2 (Bedrock) 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 V3.2 (Bedrock) vs Llama 3.1 70B (Bedrock)?
Both models are well-suited for Summarization, General chatbot. DeepSeek V3.2 (Bedrock) is particularly strong for Code generation. Llama 3.1 70B (Bedrock) is favored for 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 V3.2 (Bedrock) vs Llama 3.1 70B (Bedrock)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — DeepSeek V3.2 (Bedrock) costs $0.001545 per request and Llama 3.1 70B (Bedrock) costs $0.003230 per request. At 100,000 requests/month, that translates to $154.50 and $323.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
DeepSeek V3.2 (Bedrock) vs Llama 3.1 70B (Bedrock): Summary
When comparing DeepSeek V3.2 (Bedrock) 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 V3.2 (Bedrock) offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $154.50/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 V3.2 (Bedrock) charges $0.62/M for input tokens and $1.85/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: Both models support 128,000 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 DeepSeek V3.2 (Bedrock) or Llama 3.1 70B (Bedrock) is recommended.