GPT Image 2.5 API Pricing: Why the Newer Tier Costs Less

Newer normally means pricier. The OpenAI image endpoints available through Siray.ai run the other way. GPT Image 2.5 costs less per image than the generation before it, and its edit endpoint charges the same as its text-to-image endpoint. For teams whose work is mostly editing rather than generating from scratch, those two facts together cut the per-image bill by 60%.

Key Takeaways

• GPT Image (gen-2): $0.005 per image for text-to-image, $0.010 for edit — editing is exactly double.
• GPT Image 2.5: $0.004 per image for both text-to-image and edit — editing carries no premium at all.
• The newer generation is 20% cheaper on text-to-image and 60% cheaper on edit.
• flare and sunburst are two parallel 2.5 variants with identical request schemas and identical prices.
• No endpoint in the family exposes a seed field, so nothing here is reproducible.

The six endpoints and what they cost

Six OpenAI image endpoints are live on Siray: a text-to-image and an edit endpoint for the second generation, and the same pair for each of the two 2.5 variants.

One point deserves emphasis, because the naming invites a wrong guess: flare and sunburst are not a speed-versus-quality split. Their request schemas match field for field and their prices match to the tenth of a cent. They are two available lanes of the same tier, not a choice that changes what you can control.

Where the real gap is: editing

Text-to-image pricing shows a modest 20% improvement between generations. Editing is where the difference stops being modest.

On the second generation, the edit endpoint costs exactly twice its own text-to-image endpoint. On 2.5, editing costs the same as generating. A catalogue pass that produces 500 base images and then runs two edits over each one prices out like this:

• gen-2: (500 × $0.005) + (1,000 × $0.010) = $12.50
• 2.5: (500 × $0.004) + (1,000 × $0.004) = $6.00

Slightly more than half, and the saving scales with how edit-heavy the pipeline is. Workflows that treat generation as a first draft and editing as the real work see the full 60% cut on the part of the bill that dominates.

What you give up

Two limits are worth knowing before the price tag settles the decision.

No seed. None of the six endpoints accepts a seed value. A result that lands well cannot be re-rolled with a small prompt change and the same starting point. The working pattern is to generate a batch and select, not to iterate on one known-good output.

No documented split between the variants. Because flare and sunburst share a schema and a price, there is no parameter-level reason to prefer one. Pick on availability and on what the outputs look like for your own prompts. Any guide that assigns them different strengths is inventing the distinction.

Picking an image endpoint on Siray

Siray resells these endpoints through a single API, so moving between them is a model-string change rather than a new integration. That matters more than usual here, because the cheapest option in a catalogue shifts over time and the comparison is worth re-running. Nano Banana 2's tier structure and Qwen Image 3's pricing both sit in the same low-cost bracket, and the wider field is covered in the 2026 image generator roundup.

One API key reaches all of them, which is the practical reason to benchmark against your own prompts rather than against a spec sheet.

Create your free Siray account and run the same prompt across GPT Image 2.5, Nano Banana 2 and Qwen Image 3 before committing a pipeline to any of them.