In April 2026, OpenAI shipped GPT Image 2 with native typography rendering across 50+ languages, web-search-grounded thinking mode, and image-to-image editing with flexible multi-reference inputs (OpenAI, 2026). As of May 5, both the text-to-image and edit flows are live on Teno. The launch reshapes how we'd assemble an image stack for ad creative because GPT Image 2 finally makes text-heavy, multilingual creative feel like a first-class image-generation job.
Key Takeaways
- Both text-to-image and edit flows ship today, May 5, 2026, available on every paid plan and on the free tier at low quality.
- Multilingual typography is the headline capability. GPT Image 2 renders accurate text across 50+ scripts including Arabic, Japanese, Korean, and Devanagari (Microsoft, Azure AI Foundry Blog, April 2026).
- Three quality tiers (low / medium / high) let teams separate prompt exploration, reviewable drafts, and final renders without changing models.
- Use it alongside, not instead of, Nano Banana Pro. GPT Image 2 owns typography and precise edits; Nano Banana Pro still owns character and product-hero consistency.
This is the launch post and, until we publish a longer hands-on guide, the canonical Teno write-up on GPT Image 2: what it does, where it fits, and when to choose it over the rest of the image stack.
What is GPT Image 2, and what's actually new?
GPT Image 2 is OpenAI's April 2026 next-generation image model, released on April 21, 2026 to the API, Codex, and ChatGPT for all users (OpenAI, 2026). The launch documents native typography accuracy across 50+ languages, thinking mode with web search, multi-image variant generation up to eight per prompt, and image-to-image editing with flexible multi-reference inputs. On Teno, the ad-team subset of that surface is exposed today: prompt, image size, quality, number of images, output format, and (on edit) multi-reference image URLs.
Four capabilities matter for paid creative:
- Multilingual typography that survives small sizes. Most 2024-2025 image models could draw English text passably and butcher CJK or Arabic. GPT Image 2 renders accurate text across Arabic, Japanese, Korean, Chinese, Hindi, Bengali, Cyrillic, Devanagari, and Latin scripts (Microsoft, Azure AI Foundry Blog, April 2026). For cross-border DTC teams shipping packaging mockups or feed-card copy in 5+ markets, this collapses a Photoshop step that used to gate every AI-generated background.
- Thinking mode with web search. The model can fetch real-time references before drawing, which matters when a prompt depends on a current product, logo, or seasonal context. The trade-off is latency, so we'd reserve it for hero renders rather than batch tests.
- Up to 8 variants per prompt with consistency. A single generation returns a coherent set, not eight independent rolls — useful for grid layouts, A/B variant batches, or storyboard frames in one shot.
- Precise instruction following on multi-object scenes. GPT Image 2 holds spatial constraints ("logo top-right, product center, hand entering from frame-left") more reliably than its predecessors, which is the main reason the Teno team description calls out "fine typography" and "precise image edits."
How should teams set GPT Image 2 quality on Teno?
GPT Image 2 exposes a simple quality dial on Teno: low, medium, and high. Treat that dial as a workflow control first. Low is for prompt exploration, medium is for reviewable internal drafts, and high is for final creative where typography, product detail, and layout precision need to survive export.
The practical quality map:
- Low: fastest way to test prompt direction, rough layout, language variants, and copy placement.
- Medium: best checkpoint for creative review when the idea is close but not ready for paid placement.
- High: final render setting for packaging, multilingual social cards, hero product shots, and any asset with readable text on the canvas.
The default landscape_4_3 + high-quality setting is calibrated at 3 credits per image in Teno's May 2026 model catalog. Live credit-to-USD conversion follows your plan; see pricing for the exact rate. The more important operating rule is simpler: don't judge a prompt from one high-quality roll. Explore the idea at low or medium, then re-render the winner at high.
That low-to-high pattern mirrors how experienced video teams already test Seedance or Veo prompts: separate creative exploration from final export so the team can make better taste decisions before polishing the asset.
When should you reach for GPT Image 2 vs. Nano Banana Pro or Nano Banana 2?
For most paid-creative teams, GPT Image 2 is now the default image model for anything with text on the canvas, including packaging mockups, multilingual social cards, OOH-style ad layouts, and price/CTA overlays. Nano Banana Pro remains the right pick for recurring-character or recurring-product hero shots across a campaign, while Nano Banana 2 is a strong fit for high-volume background and lifestyle work. None of the three replaces the others; the stack splits cleanly by job.
A quick cross-model map:
| Model | Best at | Honest trade-off |
|---|---|---|
| Nano Banana 2 | Volume lifestyle creative; flexible background generation | Typography on the image is the weakest of the three |
| Nano Banana Pro | Commercial-grade character and product consistency across a campaign | Less compelling when typography is the main deliverable |
| GPT Image 2 | Typography across 50+ languages; precise multi-object scenes; multi-reference edits | Recurring character likeness drifts more than Nano Banana Pro |
The decision rule we'd give a paid creative team:
- Anything with text on the canvas → GPT Image 2. Packaging, price tags, CTAs, multilingual feed cards, OOH-style mockups.
- Recurring brand character or hero product across many frames → Nano Banana Pro. Founder cam, mascot, signature SKU.
- High-volume backgrounds and lifestyle scenes → Nano Banana 2. Strong choice when typography isn't the deliverable.
- Start-and-end frames feeding Seedance 2.0 image-to-video → any of the three, picked by which capability matters most for that specific transition.
For where this fits in the broader paid-creative stack, see our AI ad creative platform guide.
What ad-creative jobs is GPT Image 2 actually best for?
The four jobs where GPT Image 2 noticeably outperforms its peers on Teno are: multilingual social cards, packaging and label mockups, multi-object shot composition, and reference-based brand edits. All four reduce to the same underlying capability — accurate small-text rendering plus tight instruction following on spatial constraints — which is the gap OpenAI optimized this generation for (OpenAI, 2026).
A few worked examples:
- Multilingual social card (DTC, 4 markets in one batch). Prompt: a single product hero, four language variants of the same headline (EN, DE, JP, AR) requested in one generation. GPT Image 2 holds typography correctly across all four scripts; most prior models would corrupt the Arabic and produce near-glyphs in Japanese.
- Packaging mockup with regulatory copy. Skincare or supplement category, where the back-of-pack copy is small, dense, and language-specific. Generate the front and back panels in one prompt; ship to the legal review with real readable text instead of placeholder Latin lorem.
- Multi-object scene with strict layout. "Hero product center, brand logo top-right corner, accent prop at frame-left, all on a soft gradient background, soft daylight." GPT Image 2 holds the spatial constraints; earlier image models tended to migrate the logo into the center.
- Reference-based edits. Send 2-3 reference images plus a prompt to the edit endpoint and the model composes a new scene that respects the references. The cleanest use case is updating an existing hero image with new seasonal copy without regenerating the entire layout.
Our finding: Across the typography-heavy ad concepts we ran in early May 2026, GPT Image 2 usually reached ad-grade quality on the first or second roll for multilingual prompts, where the previous-generation models we'd tested often needed 4-6 retries plus manual text overlay.
For start- and end-frame anchors that feed Teno's video models, pick the image flow that exposes the model you need: Product Photo for its supported stack (including Nano Banana Pro on product-led workflows), and Asset Generator when those frames should be built with GPT Image 2 — it is only available there today.
How to use GPT Image 2 on Teno today
Open Asset Generator, pick GPT Image 2 from the model dropdown, choose between text-to-image and edit, set the size, set the quality, and write the prompt. For edit, attach 1-3 reference images alongside the prompt. Default quality is high; default size on text-to-image is landscape_4_3 and on edit is auto, which preserves the source aspect ratio.
If you're testing prompts at scale, set the quality dropdown to low for the first few rolls, then re-render the winner at high. The free trial is open — start a Teno account and test GPT Image 2 where it is strongest: text-heavy product visuals, localized social cards, and precise reference-based edits.
For the studio-level view of how GPT Image 2 fits alongside our other 13 image and video models — including the decision matrix and credit cost table for the full 14-model catalog — see the Asset Generator launch post.
Sources
- OpenAI, GPT Image 2 Model (API documentation), retrieved 2026-05-05.
- Microsoft, Introducing OpenAI's GPT-image-2 in Microsoft Foundry, Azure AI Foundry Blog, retrieved 2026-05-05.
- Teno model catalog, May 2026 (credit calibration, quality-tier multipliers, and canonical sizes). Internal documentation; live credit-to-USD conversion reflected on /pricing.
