image model comparison
GPT Image 2.6 Sunburst vs MiniMax H3-Image
GPT Image 2.6 Sunburst and MiniMax H3-Image are both current image models, from OpenAI and MiniMax. MiniMax H3-Image is 54% cheaper per 1M input tokens than GPT Image 2.6 Sunburst, $2.30 vs $5. On Arena Text-to-Image, GPT Image 2.6 Sunburst scores 1406 Elo and MiniMax H3-Image 1197 Elo (Arena, measured November 12, 2026).
- Higher Arena Text-to-Image
- GPT Image 2.6 Sunburst1406 Elo against 1197 Elo
- Lower price per 1M input tokens
- MiniMax H3-Image$2.30 against $5
- Newer release
- MiniMax H3-ImageNov 11, 2026 against Nov 4, 2026
Data verified November 15, 2026 · Dataset 2026-11-15
Side by side
GPT Image 2.6 Sunburst and MiniMax H3-Image, line by line
Prices in effect today, compared at the same tier wherever both list one. The better value in each row is highlighted.
| Fact | GPT Image 2.6 Sunburst | MiniMax H3-Image |
|---|---|---|
| Price | ||
| Price per 1M input tokens | $5 | $2.30 (better) |
| Independent benchmarks | ||
| Arena Text-to-Image | 1406 Elo (#2 of 11) (better) | 1197 Elo (#9 of 11) |
| Arena Image Edit | 1476 Elo (#3 of 10) (better) | 1359 Elo (#8 of 10) |
| Specs | ||
| Provider | OpenAI | MiniMax |
| Release date | November 4, 2026 | November 11, 2026 |
| Access | API only | API and open weights |
| Context window | Not reported | Not reported |
| Max output | Not reported | Not reported |
| Input | text, image | text, image |
| Output | image | image |
Scores:Arena · 2026-11-15
Charts
Against every current image model
Where GPT Image 2.6 Sunburst and MiniMax H3-Image land among the current models of their task, on every independent benchmark, on price and on context.
Where each stands
On Arena Text-to-Image, GPT Image 2.6 Sunburst ranks #2 and MiniMax H3-Image #9 of 11 current models. Each bar is the share of current models it beats: on score, price and context.
Independent benchmarks
Arena Text-to-Image
GPT Image 2.6 Sunburst:#2of 11
1,406 Elo · ahead of 90%
MiniMax H3-Image:#9of 11
1,197 Elo · ahead of 20%
Arena Image Edit
GPT Image 2.6 Sunburst:#3of 10
1,476 Elo · ahead of 78%
MiniMax H3-Image:#8of 10
1,359 Elo · ahead of 22%
Cost
What each costs
Example workloads at each provider's listed rates, then every other rate either one lists. The cheaper figure in each row is highlighted.
Prices, like for like
For price per 1M input tokens, GPT Image 2.6 Sunburst costs 2.2 times as much as MiniMax H3-Image, at each provider's listed rates.
Price per 1M input tokens
GPT Image 2.6 Sunburst costs 2.2× as much
- GPT Image 2.6 Sunburst
- $5
- MiniMax H3-Image
- $2.30
| Workload or rate | GPT Image 2.6 Sunburst | MiniMax H3-Image |
|---|---|---|
| Other listed rates | ||
| 1M input tokens, cached | $1.25 | Not listed |
| 1M output tokens, batch image output | $15 | Not listed |
| 1M input tokens, image input | $8 | $1.50 (better) |
| 1M output tokens, image output | $30 | $3.80 (better) |
Your own bill will differ. These figures use list prices and example workloads. The AI Model Cost Audit reviews your real usage, shortlists models that score as well for each task for less, and estimates the savings.
Launch price $100, regular price $150
Verdict
When to choose each
GPT Image 2.6 Sunburst
Where it leads
- Higher Arena Text-to-Image score, 1406 Elo vs 1197 Elo
- Higher Arena Image Edit score, 1476 Elo vs 1359 Elo
- A cached-input rate, $1.25 per 1M tokens
Best for
- Detailed compositions, brand-consistent edits and animated GIFs where quality matters most
Watch out for
- Arena rates it below GPT Image 2.5 Sunburst: 1406 against 1429 for generation and 1476 against 1519 for editing (November 12, 2026), on 2,697 and 3,493 votes so far
- Batch halves every rate, as for GPT Image 2.5: $4 per 1M image input and $15 per 1M image output tokens, for jobs that can wait
MiniMax H3-Image
Where it leads
- Lower price per 1M input tokens, $2.30 vs $5
- Open weights you can run yourself
Best for
- High-resolution product and marketing images where cost per image matters
- Teams that want to self-host or fine-tune an image model, where the license's territory rules allow it
Watch out for
- Arena rates it well below GPT Image 2.6 Sunburst: 1197 against 1406 on text-to-image and 1359 against 1476 on image editing (November 12, 2026), on 3,277 to 5,129 votes so far
- The weights' community license excludes the European Union, the United Kingdom, South Korea and the United States, and needs MiniMax's written authorization above $1 million in annual revenue or for any hosted service
- The launch-week 50% discount on 4K images ends on November 17, 2026, and MiniMax publishes no quality benchmarks of its own
From benchmark to production
Building on GPT Image 2.6 Sunburst or MiniMax H3-Image?
Public scores rarely hold on your own data. We test both models on your real tasks, then build the agent or pipeline around the one that wins.
AI Model Cost AuditLaunch price $100, regular price $150
FAQ
GPT Image 2.6 Sunburst vs MiniMax H3-Image FAQ
Which is cheaper, GPT Image 2.6 Sunburst or MiniMax H3-Image?
MiniMax H3-Image is 54% cheaper per 1M input tokens than GPT Image 2.6 Sunburst, $2.30 vs $5.
Do GPT Image 2.6 Sunburst and MiniMax H3-Image discount cached input?
GPT Image 2.6 Sunburst lists a cached-input rate of $1.25 per 1M tokens, 75% below its standard input rate. No cached-input rate is listed for MiniMax H3-Image.
Which scores higher on independent benchmarks, GPT Image 2.6 Sunburst or MiniMax H3-Image?
GPT Image 2.6 Sunburst leads on Arena Text-to-Image, 1406 Elo to 1197 Elo; GPT Image 2.6 Sunburst leads on Arena Image Edit, 1476 Elo to 1359 Elo. Scores are independent evaluations, not either vendor's launch figures.
Can I run GPT Image 2.6 Sunburst or MiniMax H3-Image myself?
MiniMax H3-Image is released as open weights you can run yourself; GPT Image 2.6 Sunburst is available through its provider's API only.
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Production evaluation
Choosing between GPT Image 2.6 Sunburst and MiniMax H3-Image?
Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.
- A head-to-head evaluation on your real workload
- Routing between models by cost and difficulty