Is o3 cheaper than Claude Opus 4.7?

On input tokens, o3 is cheaper ($2.00 vs $5.00 per million). On output tokens, o3 is cheaper. Total cost on a typical workload depends on your input:output ratio.

Which has the larger context window, o3 or Claude Opus 4.7?

Claude Opus 4.7 has a 1,000,000-token context window. o3 fits 200,000 tokens.

How do I switch from o3 to Claude Opus 4.7?

Update the model id in your API call: replace "o3" with "claude-opus-4.7". Then verify cost impact on a sample of your real prompts using a token counter.

o3 vs Claude Opus 4.7

Side-by-side comparison of o3 (OpenAI) and Claude Opus 4.7 (Anthropic). Exact API pricing per million tokens, context windows, output speed, and total cost on real-world prompts.

Specifications

Spec	o3	Claude Opus 4.7
Provider	OpenAI	Anthropic
Model id	o3	claude-opus-4.7
Input price (per 1M tokens)	$2.00	$5.00
Output price (per 1M tokens)	$8.00	$25.00
Context window	200,000	1,000,000
Output speed (tokens/sec)	~40	~30

Cost on real prompts

Total cost = (input tokens × input price) + (output tokens × output price). Numbers below use the exact pricing tables published by each provider.

Scenario	Input	Output	o3	Claude Opus 4.7	Cheaper
Short question + answer	50	150	$0.001300	$0.004000	o3
Code review on one file	500	1,500	$0.013000	$0.040000	o3
Long document summary	5,000	500	$0.014000	$0.037500	o3
Heavy reasoning task	2,000	8,000	$0.068000	$0.210000	o3
Full codebase analysis	50,000	10,000	$0.180000	$0.500000	o3

Want the exact cost for your prompt instead of these examples? Open the cost calculator pre-loaded with both models →

When to pick which

Heuristics derived from the spec table above. Always validate on your own prompts before committing — these are starting points, not verdicts.

Pick o3 for

•output-heavy workloads (long-form generation, code, summaries) — o3 is meaningfully cheaper per output token
•input-heavy workloads (long context, RAG, document QA) — o3 is cheaper per input token
•latency-sensitive UX (chat, autocompletion) — o3 streams faster (~40 vs ~30 tok/s)

Pick Claude Opus 4.7 for

•tasks needing a larger context window — claude-opus-4.7 fits 5x more tokens than o3

Switching between them

For most use cases, switching providers means updating the model id and the request shape if the providers differ. Within the same provider, it's usually a single-line change.

From o3 to Claude Opus 4.7

# Before
model = "o3"

# After
model = "claude-opus-4.7"

If the providers differ (OpenAI vs Anthropic), you'll also need to swap the SDK / endpoint URL. Cross-provider migrations usually take 30 minutes to a few hours depending on how many features (streaming, function calling, tool use) you depend on.

Calculate cost on your own prompt

The examples above use generic input/output ratios. For an exact comparison, paste your real prompt into the calculator — it counts tokens with the right tokenizer for each model and shows side-by-side cost.

Open the calculator with both models →