OpenAI vs Claude Pricing: Which AI Models Are Cheaper in 2026?
Updated 27 October 2026 by Jake Hissitt, Founder of Stob.AI.
OpenAI vs Claude pricing: the short answer
GPT-6.1 Terra costs $1 input and $5 output per million tokens—half the fresh-input/output rates of GPT-6.1 Sol and Claude Sonnet 5, and a quarter of Claude Opus 5.5’s. For simple volume, GPT-6 Luna is cheaper still at $0.10/$0.50. For difficult coding, Sol, Opus or a premium escalation model may earn their higher cost.
This is a first-party API price comparison, not a claim of equal capability. It excludes subscriptions, enterprise contracts, partner-cloud prices and tool charges. At Stob.AI, we choose models by cost per accepted outcome: retries, reasoning tokens and human corrections can matter more than list price.
Current model rates at a glance
| Model | Input / 1M | Cached input / 1M | Output / 1M | Operational role |
|---|---|---|---|---|
| GPT-6 Luna | $0.10 | $0.01 | $0.50 | Simple classification, extraction and routing |
| GPT-6.1 Terra | $1 | $0.05 | $5 | Writing, visual reasoning and computer use |
| GPT-6.1 Sol | $2 | $0.10 | $10 | Demanding coding and agents |
| Claude Haiku 4.5 | $1 | $0.10 | $5 | Fast, lightweight tasks |
| Claude Sonnet 5 | $2 | $0.20 | $10 | Balanced production |
| Claude Opus 5.5 | $4 | $0.20 | $20 | Complex agentic coding and knowledge work |
| GPT-6 Astra | $10 | $1 | $50 | Premium reasoning escalation |
| Claude Fable 5.1 | $10 | $0.25 | $50 | Highest-complexity long-horizon work |
Terra was checked against OpenAI’s 26 October release and API documentation. Claude rates above are the existing dated provider snapshot; this update does not imply every Anthropic price was newly reverified. Check Anthropic’s current pricing before committing a budget.
What changed with Terra
GPT-6.1 Terra undercuts its predecessor, GPT-5.6 Terra, at $1/$5 rather than $2/$12. Fresh input is 50% cheaper, output about 58.3% cheaper. It retains 1.05M context and 128K maximum output, with 922K maximum input. It is not a blanket replacement for Sol or Astra: OpenAI still recommends those models for the hardest coding.
OpenAI reports Terra completing Agents’ Last Exam tasks over three times faster than Sol and Astra. At maximum effort, it reports roughly nine times lower cost per task than Opus 5.5 on that evaluation. Neither figure proves the same saving on your own agents; reasoning effort, tools, task mix and completion criteria differ.
Cost of 1,000 identical requests
Assume 2,000 uncached input tokens and 500 billable output tokens per request: two million input and half a million output in total. The calculation is 2 × input rate + 0.5 × output rate. Output includes reasoning within this fixed budget; additional reasoning changes the estimate.
| Model | Standard / 1,000 requests | Batch / 1,000 | Standard / 1 million |
|---|---|---|---|
| GPT-6 Luna | $0.45 | $0.225 | $450 |
| GPT-6.1 Terra | $4.50 | $2.25 | $4,500 |
| Claude Haiku 4.5 | $4.50 | $2.25 | $4,500 |
| GPT-6.1 Sol | $9 | $4.50 | $9,000 |
| Claude Sonnet 5 | $9 | $4.50 | $9,000 |
| Claude Opus 5.5 | $18 | $9 | $18,000 |
| GPT-6 Astra | $45 | $22.50 | $45,000 |
| Claude Fable 5.1 | $45 | $22.50 | $45,000 |
Terra and Haiku have the same fresh-input/output rates in this snapshot, not necessarily the same quality. Luna costs 90% less than either in this scenario. Sol and Sonnet tie on fresh token rates; caching and task efficiency can break that tie. These are calculated estimates, not measured operating bills.
Long context: the surcharge does not always reverse the winner
Terra, Sol, Astra and Luna apply higher rates when a prompt has more than 272,000 input tokens: 2× input/cache and 1.5× output for the entire request. Claude’s listed current models have no equivalent 272K threshold. That gives Claude a simpler price structure, but does not automatically make it cheaper.
For one request with 900,000 fresh input tokens and 10,000 billable output tokens, the resulting estimates are:
| Model | Applicable input / output per 1M | Request cost |
|---|---|---|
| GPT-6.1 Terra | $2 / $7.50 | $1.875 |
| Claude Sonnet 5 | $2 / $10 | $1.90 |
| GPT-6.1 Sol | $4 / $15 | $3.75 |
| Claude Opus 5.5 | $4 / $20 | $3.80 |
| GPT-6 Astra | $20 / $75 | $18.75 |
| Claude Fable 5.1 | $10 / $50 | $9.50 |
Terra still narrowly undercuts Sonnet in this fixed-token example, while Fable is substantially cheaper than Astra. Haiku’s 200K context cannot fit this 900K request, so it is excluded rather than assigned an impossible price. Use retrieval to limit inputs when the whole collection is unnecessary.
Cached input and retention change repeated-agent costs
Terra cache reads cost $0.05 per million, Sol $0.10 and Astra $1. Terra’s Standard cache writes cost $1.25 for 30-minute retention or $2.50 for 12 hours, before long-context multipliers. Claude’s retention windows and writes differ: Sonnet’s five-minute writes are $2.50, Opus 5.5’s $5, and Fable 5.1’s $12.50; one-hour retention is priced separately.
For 1,000 requests with 20K input tokens each, half cached, and 2K billable output tokens each, exclude initial cache writes and tool charges:
| Model | 10M fresh input | 10M cached input | 2M output | Total |
|---|---|---|---|---|
| GPT-6.1 Terra | $10 | $0.50 | $10 | $20.50 |
| GPT-6.1 Sol | $20 | $1 | $20 | $41 |
| Claude Sonnet 5 | $20 | $2 | $20 | $42 |
| Claude Opus 5.5 | $40 | $2 | $40 | $82 |
| GPT-6 Astra | $100 | $10 | $100 | $210 |
| Claude Fable 5.1 | $100 | $2.50 | $100 | $202.50 |
Actual cache hits require reusable prefixes and compatible retention. Do not budget every input as cached, or ignore write fees when rebuilding a cache frequently.
Processing mode and regional charges
Terra Batch and Flex rates are 50% below Standard. Batch trades immediacy for asynchronous processing; Flex trades speed and availability for price. Fast mode is twice Standard: $2 input/$10 output. Eligible regional processing adds 10%. Anthropic also offers Batch discounts; region-specific processing and partner endpoints can have separate rates.
Why token price is not total workflow cost
- Different tokenizers: identical documents can generate different billed input counts.
- Reasoning and retries: a shorter visible answer may still consume substantial output tokens.
- Tool calls: search, containers and external services add separate charges.
- Human correction: a cheaper model that needs repeated repairs can cost more overall.
- Latency: evaluate elapsed time for the complete workflow, not a launch benchmark’s speed ratio.
Set one acceptance standard, run the same representative tasks, and compare total cost divided by accepted completions. Do not generalise Terra’s vendor-reported cost advantage on Agents’ Last Exam to every Claude workload.
Recommended routing pattern
| Work | Starting shortlist | Escalate when |
|---|---|---|
| Simple high-volume records | GPT-6 Luna or Haiku 4.5 | Required fields, classification or evidence checks fail |
| Writing, screenshots and application tasks | GPT-6.1 Terra or Sonnet 5 | Quality or tool-use reliability falls short |
| Demanding coding and long agents | GPT-6.1 Sol or Opus 5.5 | Validated difficult tasks still fail |
| Highest-complexity exceptions | Astra or Fable 5.1 | A human review is required after repeated failure |
Keep workflow state, permissions and irreversible actions in the system around the model. The model interprets information and proposes decisions; approvals and deterministic checks control what actually happens.
Frequently asked questions
Is Terra cheaper than Claude?
Its $1/$5 fresh-input/output rates are half Sonnet 5 and a quarter Opus 5.5 in this snapshot; they equal Haiku 4.5. That is a token-price comparison, not equal-performance evidence.
Is Terra replacing Sol or Astra?
No. OpenAI still recommends Sol and Astra for the most complex coding. Terra targets fast visual reasoning, computer use and writing.
Is Claude always cheaper above 272K tokens?
No. Claude avoids that surcharge, but Terra can still be cheaper than Sonnet at identical token counts. Price the actual request, including output and cache.
Which model should a business choose?
The least expensive one that reliably meets the workflow’s acceptance criteria. Use the others as tested escalation paths, not default upgrades.
Final verdict
Terra gives OpenAI a compelling everyday tier below Sol, while Luna remains the lower-price route for simple volume. Claude’s strengths must be evaluated on completion quality, caching and long-context work—not assumed from price structure alone. Compare the OpenAI pricing guide, Claude pricing guide and model comparison tool.
Sources checked 27 October 2026: OpenAI’s GPT-6.1 Terra announcement, Terra API specifications and OpenAI API pricing. Benchmark claims below are OpenAI-reported, not independent Stob.AI measurements.