Sold by: OpenAI
Deployed on AWS
AWS Free Tier
OpenAI GPT-6.1 Sol brings intelligence approaching GPT-6 Astra to everyday work on Amazon Bedrock. Build and scale capable agents for coding, computer use, and professional workflows at Sol pricing.
Overview
OpenAI GPT-6.1 Sol is available on Amazon Bedrock, bringing stronger reasoning to agentic coding, computer use, and professional work. A major upgrade to GPT-6 Sol, it approaches GPT-6 Astra on several demanding evaluations, with standard input and output token prices roughly one fifth those of GPT-6 Astra. Investigate complex codebases, build features, debug issues, and iterate on solutions with more room to scale. Use GPT-6.1 Sol with Codex on Amazon Bedrock across investigation, implementation, and testing. Turn complex information into action with agents that analyze documents, use tools, and complete workflows across business systems. Build internal tools that synthesize documents and applications that evaluate multiple inputs. Explicit prompt caching on Amazon Bedrock supports workloads that reuse context across repeated requests. Run these workloads with the performance, scalability, security, and reliability of Amazon Bedrock, using established AWS controls to govern access and audit model activity.
Highlights
- Intelligence approaching GPT-6 Astra on several demanding evaluations at Sol pricing, with standard input and output token prices roughly one fifth those of GPT-6 Astra.
- Stronger agentic coding, computer use, and professional work. Investigate codebases, build features, debug issues, analyze complex documents, and complete workflows across business tools.
- Build and scale agents on Amazon Bedrock with explicit prompt caching, production infrastructure, and established AWS controls for access governance and auditability.
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/unit |
|---|---|
input_tokens_standard | $2.20 |
input_tokens_global_standard | $2.00 |
input_tokens_global_priority | $4.00 |
input_tokens_global_flex | $1.00 |
output_tokens_global_standard | $10.00 |
output_tokens_global_priority | $20.00 |
output_tokens_global_flex | $5.00 |
cache_read_tokens_global_standard | $0.10 |
cache_read_tokens_global_priority | $0.20 |
cache_read_tokens_global_flex | $0.05 |
Dimensions summary
You pay per token used, with no upfront commitment. Charges split into input tokens, output tokens, cache read tokens, and cache write tokens (30-minute). Each token type is priced separately, so reading cached context costs differently than fresh input or generated output. Every token type also comes in processing modes: standard, priority, and flex. Some dimensions add a global option or a long-context option for larger prompts. You mix and match these dimensions based on request volume, speed needs, and context size. Total cost scales directly with how many tokens your workload consumes across each category.
Top-of-mind questions for buyers
A token is a small chunk of text the model reads or writes, roughly a few characters. Input tokens cover the text you send. Output tokens cover the text generated. Cache read and cache write tokens meter reused context. Each type is counted and priced separately per token consumed.
Each mode meters the same token types but at its own rate. Priority targets faster responses. Flex targets cost-sensitive, high-volume work that tolerates slower processing. Standard sits between them. You pick a mode per request, and charges follow that mode's rate for every token in the call.
Cache write tokens meter storing reused context for a 30-minute window. Cache read tokens meter pulling that stored context back on later requests. Reading cached content is priced separately from fresh input tokens. Higher cache reuse shifts more of your bill toward lower-rate cache read tokens.
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