Llama 3.1 70B (Bedrock) vs o3 (Azure): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Llama 3.1 70B (Bedrock) (AWS Bedrock) and o3 (Azure) (Azure OpenAI). 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 (Bedrock) at $32.30/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestLlama 3.1 70B (Bedrock) | AWS Bedrock | $32.30 | $0.003230 | $19.50 | $12.80 | 46.2% | Alerts coming soon |
o3 (Azure) | Azure OpenAI | $60.00 | $0.006000 | $20.00 | $40.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Llama 3.1 70B (Bedrock) | o3 (Azure) | Cheaper |
|---|---|---|---|
| Input (standard) | $1.95/M | $2.00/M | Llama 3.1 70B (Bedrock) |
| Output | $2.56/M | $8.00/M | Llama 3.1 70B (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 | Llama 3.1 70B (Bedrock)Monthly | o3 (Azure)Monthly | Llama 3.1 70B (Bedrock)Per request | o3 (Azure)Per request |
|---|---|---|---|---|
| 1K requests/mo | $3.23 | $6.00 | $0.003230 | $0.006000 |
| 10K requests/mo | $32.30 | $60.00 | $0.003230 | $0.006000 |
| 100K requests/mo | $323.00 | $600.00 | $0.003230 | $0.006000 |
| 1M requests/mo | $3,230.00 | $6,000.00 | $0.003230 | $0.006000 |
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 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
When to Choose o3 (Azure)
by Azure OpenAI
- Code generation
- Data extraction
- Summarization
Input / 1M tokens
$2.00/M
Output / 1M tokens
$8.00/M
Context window
200,000
Tier
reasoning
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 70B (Bedrock) | o3 (Azure) |
|---|---|---|
| Context window | 128,000 tokens | 200,000 tokens |
| Max output tokens | 4,096 tokens | 100,000 tokens |
| Performance tier | Mid | Reasoning |
| Vision / image input | No | Yes |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | No | No |
| Batch API (50% discount) | Yes | No |
| Extended reasoning | No | Yes |
| 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.
o3 (Azure) notes
o3 reasoning model via Azure OpenAI Service. Best for complex analytical tasks requiring deep reasoning. Azure deployment adds enterprise security and compliance.
Frequently Asked Questions
Is Llama 3.1 70B (Bedrock) cheaper than o3 (Azure)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Llama 3.1 70B (Bedrock) costs $323.00/month versus $600.00/month for o3 (Azure) — a 46% 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 (Bedrock) or o3 (Azure)?
o3 (Azure) has a larger context window at 200,000 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 Llama 3.1 70B (Bedrock) and o3 (Azure) support the Batch API?
Llama 3.1 70B (Bedrock) supports the Batch API (50% discount for async processing), while o3 (Azure) 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 o3 (Azure)'s standard rate.
Which model offers better prompt caching?
Neither Llama 3.1 70B (Bedrock) nor o3 (Azure) 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 70B (Bedrock) vs o3 (Azure)?
Both models are well-suited for Summarization. Llama 3.1 70B (Bedrock) is particularly strong for General chatbot, Rag Retrieval. o3 (Azure) is favored for Code generation, Data extraction. 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 (Bedrock) vs o3 (Azure)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Llama 3.1 70B (Bedrock) costs $0.003230 per request and o3 (Azure) costs $0.006000 per request. At 100,000 requests/month, that translates to $323.00 and $600.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Llama 3.1 70B (Bedrock) vs o3 (Azure): Summary
When comparing Llama 3.1 70B (Bedrock) and o3 (Azure) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Llama 3.1 70B (Bedrock) offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $323.00/month, compared to $600.00/month for o3 (Azure).
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Llama 3.1 70B (Bedrock) charges $1.95/M for input tokens and $2.56/M for output tokens. o3 (Azure) charges $2.00/M input and $8.00/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: o3 (Azure) supports up to 200,000 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.
Related Comparisons
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Relevant Use Cases
See cost recommendations for workloads where Llama 3.1 70B (Bedrock) or o3 (Azure) is recommended.