Is GPT-4o-mini (2024-07-18) a good deal?
Whether anything in this catalogue beats GPT-4o-mini (2024-07-18) on both quality and price, and what you give up if it does. A computation on the current catalogue, not an opinion.
12 undominated of 145 · Oct 6, 2026
As of Oct 6, 2026, GPT-4o-mini (2024-07-18) is dominated for Balanced on LMArena. GPT-6 Luna scores 105.1 higher and costs 24% less, with a covering envelope. 12 of 145 rated, priced standard models are undominated.
Inspect model evidence Compare differences & requirements
GPT-6 Luna is both better and cheaper than GPT-4o-mini (2024-07-18): 105.1 points higher on LMArena and 24% less per million tokens, $0.063 cheaper at this mix.
LMArena Elo · higher is better
Scale starts at 1040 Elo
1286.4
Effective $/M · Balanced · lower is better
$0.263/M
LMArena Elo · higher is better
Scale starts at 1040 Elo
1391.5
Effective $/M · Balanced · lower is better
$0.200/M
GPT-4o-mini (2024-07-18) takes text, image, file, returns up to 16,384 tokens from a 128,000-token context, and is listed by 1 seller.
Compared against 145 rated, priced models on this lens: 2 models dominate it and give up nothing, 5 more dominate it but give something up. GPT-4o-mini (2024-07-18) scores 1286.4 at $0.263 per million tokens for this mix.
Envelope-safe replacements
Each row scores at least as high, costs no more, and covers this model’s context, output, modalities, tools, and reasoning. A cheaper narrower model is not listed here.
| Model | LMArena | Effective $/M | You save |
|---|---|---|---|
| GPT-6 Luna | 1391.5 +105.1 | $0.200/M | 24% |
| GPT-5 Nano | 1320.0 +33.6 | $0.138/M | 48% |
Higher score, lower price, named losses
Not a drop-in. The loss is why these are not a recommendation.
| Model | LMArena | Effective $/M | You give up |
|---|---|---|---|
| GLM 5.3 Flash | 1469.6 | $0.238/M | file |
| DeepSeek V4.1 Flash | 1462.5 | $0.182/M | file |
| MiMo-V2.6-Flash | 1456.4 | $0.175/M | file |
| Gemma 4 31B | 1443.4 | $0.205/M | file |
| Hy3 | 1440.7 | $0.231/M | image, file |
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Constraint: replacements must preserve the model’s capabilities; any losses remain named trade-offs.
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