Ideogram 4.5 vs Nano Banana 2 Lite: Six Times the Price, Nineteen Elo

Ideogram 4.5 and Nano Banana 2 Lite are a useful pair precisely because nobody asked for this comparison. The first, Ideogram 4.5, shipped on 30 September 2026 as a closed, credit-metered precision-editing model with a price ladder that tops out at $0.22 an image. The second, Nano Banana 2 Lite — the vendor's Gemini 3.1 Flash Lite Image, in production since 30 June 2026 — makes a 1K image for $0.034 flat, and about half that in batch. Put them on the same leaderboard and the expensive one is ranked 23rd in editing at 1,064 Elo while the cheap one is 26th at 1,045. Nineteen points of Elo, six and a half times the price. On the text-to-image board the order reverses outright and the gap widens to more than eighty points. So the honest question is not which is better. It is what you are actually buying when you pay the extra nineteen cents, and whether your workload needs it.

What each model actually is

The two products are built on opposite theories of the customer. Ideogram 4.5 is a specialist tool sold on a behaviour: localised changes to an existing image, with the surrounding pixels preserved rather than re-synthesised, run repeatedly on the same file. Ideogram's own launch material leads with a 4,016 × 6,016 demonstration — a 24.2-megapixel source edited in place, without downscaling first — and argues that this is what makes the edits survive a close-up or a large-format print. Four rendering speeds (Turbo, Balanced, Quality, High) set the price; resolution does not, which is an unusual choice worth noting. It is closed, hosted, and metered by credits, and no open weights have been published for it.

Nano Banana 2 Lite is the opposite bet. It is Google's deliberately throttled tier: the same Gemini image stack, capped hard at 1K output, with 2K and 4K reserved for the tiers above it. Google's own documentation names its weak spots rather than hiding them — small text, dense infographics, and character consistency across multiple images — and prices it as a volume instrument, $0.034 per 1K image, with a batch path at roughly $0.0168. It runs in about four seconds per 1K image, which Google states is about 2.7× faster than Nano Banana 2. Every output carries a mandatory SynthID watermark.

Set the two feature sets side by side, and the shape of the trade is clear:

• Output ceiling — Ideogram 4.5 renders natively at 2K (2,048 pixels on the long edge at the top setting) and demonstrates in-place editing on a 24.2 MP source, while Nano Banana 2 Lite is capped at 1K with no path upward inside that model.

• Pricing shape — a five-step ladder from $0.008 to $0.22 for Ideogram, against a single flat $0.034 for Lite with a batch discount.

• Speed — Lite publishes roughly four seconds per 1K image; Ideogram publishes no latency figure for any of its four speeds.

• Provenance — every Lite output is SynthID-marked by default; Ideogram has not described an equivalent requirement for 4.5.

• Open weights — none published for either model, though Ideogram has said it plans to release 4.5's weights eventually.

The price ladder against a flat rate

Rate cards quoted in different units hide the real ratio, so normalise both to a thousand images. Nano Banana 2 Lite lands at about $34 per 1,000 at list, or roughly $17 in batch — which is the figure Artificial Analysis's own price column reproduces independently at $33.60 per 1,000. Ideogram 4.5 at its headline configuration, High with a source image, is $220 per 1,000. That is $0.186 of difference on every single picture, a ratio of 6.5× at list and 13× against batch.

The wrinkle is that the ladder lets you walk down it, and the comparison changes materially when you do. At Medium, Ideogram charges $0.06 — under twice Lite's list rate. At Low it is $0.03, and at Very Low $0.008, comfortably cheaper than Lite on a per-image basis. So the "six times the price" framing is true only at the setting that buys the thing Ideogram is actually selling: precise localised editing on a large source file. If your workload is one-shot generation of a fresh 1K image with no edit step, you would be buying the wrong tier of the wrong model, and the price columns invert.

Where the two boards disagree

This is the most interesting result in the pairing, and it only appears if you read both of Artificial Analysis's image boards instead of the one that flatters your argument.

On the editing board the two models are effectively tied. Ideogram 4.5 (High) sits 23rd at 1,064 Elo from 2,459 samples; Nano Banana 2 Lite sits 26th at 1,045 Elo from 7,420 samples. Nineteen points is inside the overlap of their published intervals — Ideogram's run spans 1,054 to 1,074, Lite's 1,037 to 1,053 — so the honest reading is that on single-edit quality the model costing six times as much is not measurably better, and it has one third of the evidence behind its number.

On the text-to-image board the same two models separate sharply, in the other direction. Nano Banana 2 Lite ranks 13th at 1,096 Elo from 17,340 samples. Ideogram 4.5 (High) ranks 34th at 1,013 from 2,270 samples. That is an 83-point gap favouring the model that costs a sixth as much, and it is roughly five times the width of the editing gap in the opposite direction.

Both figures are independent, both come from the same voting arena, and they point the same way: Nano Banana 2 Lite is the better general-purpose image generator of the two, by a margin that is not close, while Ideogram 4.5 at best draws level on editing while charging a multiple. Two further numbers sharpen that. Ideogram 4.5's text-to-image score of 1,013 is barely above the 1,011 posted by Ideogram 4.0 back in June, so the generation side of the model is close to a step sideways. And the board's own price column converts Ideogram's editing runs at $220 per 1,000 against Lite's $33.60 — the arena is paying six times as much to break even.

Resolution: the one gap that is not close

Everything above is a close call or an argument. This is not. Ideogram 4.5 takes a 4,016 × 6,016 source — 24.2 megapixels — and edits it without downscaling first, which means the edited region can be dropped back into the original and printed at size. Nano Banana 2 Lite cannot do this at any price. Its ceiling is 1K, and the 2K and 4K paths that would let it try live on Google's higher tiers, not on the Lite model.

The practical consequence is that these two models are not interchangeable for a whole class of work, and the price difference is irrelevant to that class. If your source file is a 24-megapixel photograph and your edit is a localised retouch that has to hold up in print, Lite is not a cheaper option — it is not an option. You would be reaching for Ideogram 4.5, or for Nano Banana Pro on Google's side, and the interesting comparison becomes Ideogram 4.5 against Nano Banana Pro rather than against Lite. Lite's 1K cap is a deliberate product boundary, not an oversight, and it is the single cleanest differentiator in this matchup.

Speed: one number published, one not

Google publishes a latency figure for Nano Banana 2 Lite — about four seconds per 1K image, roughly 2.7× faster than Nano Banana 2 — and it is credible, because a 1K-only model on a lite tier is exactly where the engineering budget went. Ideogram publishes nothing comparable. There is no latency figure attached to Turbo, Balanced, Quality or High, which is a real gap in the buyer's information: the fast setting is named "Turbo" and the expensive one is not, but nothing on the public record says how much slower High is than Lite's four seconds, or than Ideogram's own $0.008 tier.

That matters more than it looks. At scale, the per-image price and the per-image latency compound in opposite directions: a six-times-cheaper image that takes six times as long is a different product, not a better deal. For Lite, Google has given you the number. For Ideogram, the only defensible statement is that it is unpublished, and any pipeline that assumes otherwise is guessing.

The parts nobody can measure

Both models come with a claim that no public benchmark tests, and it is worth naming them separately because they fail in different ways.

Ideogram's is multi-turn drift. Its launch material asserts that competing outputs "become unusable within a few edits" while 4.5 "stays clean edit after edit" — a specific, falsifiable-sounding proposition about how far pixels walk from the original across a sequence of edits. Artificial Analysis scores single-edit quality in its editing arena and single-generation quality in its text-to-image arena. Multi-turn drift is not an axis on either board, which means that the one behaviour Ideogram 4.5 is really selling cannot currently be verified by anyone outside Ideogram. It may well be true. It is, today, an assertion.

Note also which models Ideogram chose to compare against: its own launch asset names GPT Image 2.5 Sunburst, Nano Banana Pro and Nano Banana 2. It does not name Nano Banana 2 Lite — the cheaper Google tier that matches it on the editing board and beats it on generation. That is a sensible piece of marketing and a poor guide to the purchase decision, and it is the reason this comparison is worth writing separately from the one Ideogram staged.

Google's claim runs the other way and is easier to check, because Google published the limitations itself. Nano Banana 2 Lite is documented as weak on small text, dense infographics and character consistency across a series of images. Those are exactly the three failure modes where a 1K cap bites hardest — a dense infographic at 1,024 pixels has nowhere for the detail to go — so the vendor description and the specification agree. The editing board's 19-point tie is consistent with that too: Lite competes on single edits, on modest sources, at speed, and runs out of room when the task needs resolution.

Getting either of them

Neither model is on OrcaRouter's catalogue today, and it is worth saying so plainly rather than implying otherwise. Our public model API returns "model not found" for both Ideogram 4.5 and the Gemini 3.1 Flash Lite Image identifier behind Nano Banana 2 Lite. Ideogram 4.5 is served through Ideogram's own app and API and through its launch partners; Nano Banana 2 Lite is served through Google's own API and the Gemini app and, like most Google image models, through several third-party platforms.

What we do carry is the tier directly above Lite, and it is the more useful route for most of the workloads this article describes:

• google/gemini-3.1-flash-image-preview — Nano Banana 2 itself, $0.151 per call, the model whose 2K and 4K paths Lite's 1K cap defers to.

• google/gemini-3-pro-image-preview — Nano Banana Pro, $0.24 per call, the Google tier that competes with Ideogram 4.5 on high-resolution editing.

• grok/grok-imagine-image and the GPT-Image line — the other image generators on the same key, priced per call.

That is the shape of the routing argument, and it is the reason this matters to a comparison of two models we do not host. All of it runs behind one OpenAI-compatible endpoint and one key, at 0% markup — we pass the provider's own list price straight through, so a vendor price cut lands in your bill the same day rather than at the next contract renewal. Automatic failover means an image route that stalls does not stall your pipeline; the routing DSL lets you pin a request to a tier when the resolution ceiling is the thing you care about, and model fusion lets a single call fall through several models when the cheap one is not good enough. For a workload like this one, where the right answer is genuinely different at 1K and at 24 megapixels, that is the practical value: one key, both tiers, and the ability to route the same job to a different model when the resolution changes.

Which one belongs in your pipeline

The decision falls out of the two boards rather than out of the price list, which is the useful lesson here.

• Choose Nano Banana 2 Lite if your workload is high-volume generation of 1K images with light or no editing, if four seconds an image matters, or if you are producing consumer-scale collateral where $34 per thousand against $220 per thousand is the entire budget conversation. On the evidence, it is the better generator of the two by a wide margin and a statistical tie on single edits.

• Choose Ideogram 4.5 if your inputs are large files that must be edited in place and stay print-viable — a 24-megapixel source edited at native resolution is a capability Lite does not have at any price — or if you have measured multi-turn drift in your own pipeline and need the model built around it. Buy the High tier with a source image, because that is the configuration whose behaviour you are paying for.

• Do not choose either for a mixed pipeline on price alone. At 1K, Ideogram's Low and Very Low tiers undercut Lite on the sticker; at 24 megapixels, Lite is not in the running. Those are two different jobs wearing the same comparison.

What the pairing really shows is that a 6.5× price difference bought 19 Elo on one board and lost 83 Elo on the other. That is not a premium for quality — it is a premium for a resolution ceiling and a drift behaviour, one of which is measurable and one of which nobody outside Ideogram has measured yet. Read the boards, decide which of those two things your pipeline actually needs, and route accordingly.