Best LLMs for Content To Image Prompt Generation
Converts supplied content and optional visual context into a detailed, model-agnostic image-generation brief describing subject, composition, style, palette, mood, and constraints. Illustrative uses include preparing visual briefs for a software launch, product campaign, customer
Run this task on Fronset — request an invitation
Models
Frontier on this task: Claude Opus 5.5 at 8.90 / 10. Quality bar at 90%: 8.01.
point-estimate floor (CI low) · upper CI (less certain) · Bars sorted by blended cost; best-value model first. Greyed rows are MEDIUM+ models whose point estimate does not clear the bar.
| Model | Quality score | CI low | Cost / 1k runs | vs best value |
|---|---|---|---|---|
| Xiaomi MiMo V2.6 Flash | 8.48 / 10 | 8.29 | $0.22 | best value |
| GPT-6 Luna | 8.75 / 10 | 8.61 | $0.25 | 1.1x more expensive |
| Claude Haiku 5.5 | 8.52 / 10 | 8.33 | $0.36 | 1.6x more expensive |
| MiniMax M3 | 8.26 / 10 | 8.06 | $1.16 | 5.2x more expensive |
| Tencent Hy3 | 8.17 / 10 | 8.04 | $2.55 | 11x more expensive |
| Thinking Machines Inkling Small | 8.68 / 10 | 8.32 | $2.75 | 12x more expensive |
| Gemini 3.8 Flash | 8.02 / 10 | 7.83 | $3.21 | 14x more expensive |
| Qwen 3.7 Plus | 8.37 / 10 | 8.29 | $3.48 | 16x more expensive |
| NVIDIA Nemotron-3 Ultra 550B | 8.36 / 10 | 8.12 | $3.92 | 18x more expensive |
| GLM-5.3 Flash | 8.79 / 10 | 8.63 | $4.46 | 20x more expensive |
| GPT-6 Sol | 8.83 / 10 | 8.66 | $4.65 | 21x more expensive |
| Claude Sonnet 5.5 | 8.76 / 10 | 8.61 | $7.10 | 32x more expensive |
| Thinking Machines Inkling | 8.78 / 10 | 8.57 | $10.42 | 47x more expensive |
| Claude Opus 5.5 | 8.90 / 10 | 8.75 | $13.98 | 63x more expensive |
| Meta Muse Spark 1.3 | 8.16 / 10 | 7.89 | $15.03 | 68x more expensive |
| Moonshot Kimi K3 | 8.65 / 10 | 8.52 | $21.06 | 95x more expensive |
| Grok 4.7 | 8.76 / 10 | 8.59 | $25.48 | 115x more expensive |
| Tencent Hy4 Preview | 8.56 / 10 | 8.32 | $25.58 | 115x more expensive |
| Qwen 3.8 Max | 8.42 / 10 | 8.28 | $29.00 | 130x more expensive |
| GLM-5.3 | 8.86 / 10 | 8.72 | $45.13 | 203x more expensive |
| Qwen 3.8 Flash | 7.83 / 10 | 7.59 | $4.83 | 22x more expensive |
| NVIDIA Nemotron 3.5 Lightning | 7.17 / 10 | 6.83 | $0.78 | 3.5x more expensive |
| NVIDIA Nemotron-3 Nano 30B-A3B | 7.02 / 10 | 6.70 | $0.37 | 1.7x more expensive |
| DeepSeek V4.1 Flash | 7.96 / 10 | 7.75 | $1.30 | 5.9x more expensive |
| Gemini 3.5 Flash Lite | 7.25 / 10 | 7.04 | $0.64 | 2.9x more expensive |
Cost breakdown
| Model | Quality | Confidence | Cost / 1k runs | Overpay | Mode |
|---|---|---|---|---|---|
| Xiaomi MiMo V2.6 Flash ★ Xiaomi MiMo | 8.48 / 10 CI [8.29, 8.67] | RANKED | $0.22 | best value | batch |
| GPT-6 Luna OpenAI | 8.75 / 10 CI [8.61, 8.89] | RANKED | $0.25 | 1.1x | batch |
| Claude Haiku 5.5 Anthropic | 8.52 / 10 CI [8.33, 8.70] | RANKED | $0.36 | 1.6x | batch |
| MiniMax M3 OpenRouter | 8.26 / 10 CI [8.06, 8.45] | RANKED | $1.16 | 5.2x | batch |
| Tencent Hy3 OpenRouter | 8.17 / 10 CI [8.04, 8.30] | RANKED | $2.55 | 11x | batch |
| Thinking Machines Inkling Small OpenRouter | 8.68 / 10 CI [8.32, 9.05] | MEDIUM | $2.75 | 12x | batch |
| Gemini 3.8 Flash Gemini | 8.02 / 10 CI [7.83, 8.22] | RANKED | $3.21 | 14x | batch |
| Qwen 3.7 Plus Alibaba Cloud (DashScope) | 8.37 / 10 CI [8.29, 8.46] | RANKED | $3.48 | 16x | batch |
| NVIDIA Nemotron-3 Ultra 550B OpenRouter | 8.36 / 10 CI [8.12, 8.59] | HIGH | $3.92 | 18x | batch |
| GLM-5.3 Flash Z.AI | 8.79 / 10 CI [8.63, 8.95] | RANKED | $4.46 | 20x | batch |
| GPT-6 Sol OpenAI | 8.83 / 10 CI [8.66, 8.99] | RANKED | $4.65 | 21x | batch |
| Claude Sonnet 5.5 Anthropic | 8.76 / 10 CI [8.61, 8.91] | RANKED | $7.10 | 32x | batch |
| Thinking Machines Inkling OpenRouter | 8.78 / 10 CI [8.57, 8.98] | HIGH | $10.42 | 47x | batch |
| Claude Opus 5.5 best Anthropic | 8.90 / 10 CI [8.75, 9.04] | RANKED | $13.98 | 63x | batch |
| Meta Muse Spark 1.3 OpenRouter | 8.16 / 10 CI [7.89, 8.44] | HIGH | $15.03 | 68x | batch |
| Moonshot Kimi K3 Moonshot AI | 8.65 / 10 CI [8.52, 8.79] | RANKED | $21.06 | 95x | batch |
| Grok 4.7 xAI | 8.76 / 10 CI [8.59, 8.93] | RANKED | $25.48 | 115x | batch |
| Tencent Hy4 Preview OpenRouter | 8.56 / 10 CI [8.32, 8.80] | HIGH | $25.58 | 115x | batch |
| Qwen 3.8 Max Alibaba Cloud (DashScope) | 8.42 / 10 CI [8.28, 8.55] | RANKED | $29.00 | 130x | batch |
| GLM-5.3 Z.AI | 8.86 / 10 CI [8.72, 8.99] | RANKED | $45.13 | 203x | batch |
Overpay shows how much more you pay than the best-value model that clears the quality bar (marked ★) — the best-value good-enough option. "16x" means you overpay 16× — 16× that reference for no quality benefit above the bar. Typical call shape for this task: 2868 input tokens → 1255 output tokens, EMA-tracked from production traffic. Cost is the observed, all-in $ per 1,000 task runs: each model's own measured usage on this task — output verbosity, thinking/reasoning tokens, cache reads and writes, and the spend on its billed failures — priced at current list rates and adjusted by the billing overhead we actually reconcile against provider invoices. Models that answer tersely cost what they actually cost; models that think at length pay for it. Not comparable to providers' advertised $/1M list rates — this is what running the task costs, not a per-token price.
Evaluation rubric
Judge source-to-concept relevance, visual specificity, compositional coherence, practical usefulness to an image model, consistency with supplied context, and avoidance of unsupported or contradictory details.
Output schema
Every answer on this task is checked against this JSON Schema, whichever model wrote it. An answer that doesn't fit counts as a model failure, and the call is retried on another model.
{
"description": "Output model for generating an image prompt for the analysis report.",
"properties": {
"image_prompt": {
"description": "A detailed, vivid description of the image to be generated.",
"title": "Image Prompt",
"type": "string"
}
},
"required": [
"image_prompt"
],
"title": "ImagePromptGenerationOutput",
"type": "object"
}Prompt templates
The published template for this task.
default ·
LLMB_CONTENT_TO_IMAGE_PROMPT_GENERATION_SYSTEM +
LLMB_CONTENT_TO_IMAGE_PROMPT_GENERATION_USER
(567 calls in window)
System prompt
You write image briefs. Given source material, produce one self-contained brief that a text-to-image model will render. The brief is the deliverable: the image is generated downstream from your words alone, so whatever you leave unsaid is left to the image model. Do not name a particular image model unless the caller asks.
Derive a visual concept from the source’s central idea rather than illustrating every detail. Cover subject, setting, composition, visual hierarchy, style, palette, lighting, mood, aspect or use context, and explicit exclusions.
SURFACE BRIEF — the image's destination, and the art direction it requires. These rules are authoritative wherever they are more specific than the general guidance above, including where they permit something it discourages:
{image_brief_profile}
Except where the surface brief says otherwise, avoid unsupported logos, real-person likenesses, legible text, charts, and sensitive imagery. Treat empty optional values as absent and return only the requested result. Your response must conform exactly to this output schema: {schema_json_string}.
User prompt
Inputs — subject_name: {subject_name}; subject_code: {subject_code}; report_content: {report_content}; reference_context: {reference_context}; topic_name: {topic_name}; topic_description: {topic_description}; context: {context}. Use only these inputs to complete the task defined by the system prompt.