AI Recommended Models

Recommended Models

Cheapest vision-capable models suitable for FindRomCover's AI Assist (synchronous chat completions, image input, text/JSON output).

Source: OpenRouter GET /api/v1/models — 446 models total, 275 accept image input (checked 2026-09-20). Prices are USD per million tokens (input / output), ordered by input price. FindRomCover's current OpenRouter default is qwen/qwen3.7-flash.

Models

#	Model ID	Input $/M	Output $/M	Context	JSON mode	Notes
1	qwen/qwen3.7-flash	$0.03	$0.13	1M	response_format	Cheapest overall; vision-language reasoning model from Alibaba; ~$0.21 per 1,000 picks
2	google/gemma-3-4b-it	$0.05	$0.10	131k	response_format	Cheapest output tokens; small but genuinely multimodal
3	google/gemma-3-12b-it	$0.05	$0.15	131k	response_format	Same input price as 4B with better quality
4	openai/gpt-5-nano	$0.05	$0.40	400k	structured outputs + response_format	Most reliable JSON parsing; smallest GPT-5 variant
5	inclusionai/ling-3.0-flash-vl	$0.06	$0.18	131k	response_format	Vision-language specialist (124B MoE / 5.5B active)
6	amazon/nova-lite-v1	$0.06	$0.24	300k	prompt-only JSON	Proven for cover picking — very reliable in real batch runs; solid low-cost multimodal; 5k max output tokens
7	qwen/qwen3.5-flash-02-23	$0.065	$0.26	1M	response_format	1M context
8	~z-ai/glm-flash-latest	$0.075	$0.25	1.3M	response_format	1.3M context
9	bytedance-seed/seed-1.6-flash	$0.075	$0.30	262k	response_format	262k context
10	google/gemma-3-27b-it	$0.08	$0.45	131k	response_format	Larger Gemma 3
11	mistralai/mistral-small-3.2-24b-instruct	$0.09	$0.25	256k	response_format	256k context
12	google/gemma-4-26b-a4b-it	$0.09	$0.30	262k	response_format	MoE variant of Gemma 4
13	google/gemma-4-31b-it	$0.09	$0.34	262k	response_format	Best value of the Gemma 4 family
14	qwen/qwen3.5-9b	$0.10	$0.15	262k	response_format	262k context; text, image and video input
15	meta-llama/llama-4-scout	$0.10	$0.30	1.3M	response_format	1.3M context
16	google/gemini-2.5-flash-lite	$0.10	$0.40	1M	response_format	Known-good quality; per-image pricing
17	qwen/qwen3.8-27b	$0.20	$2.50	1M	response_format	Large Qwen vision model
18	thinkingmachines/inkling-small	$0.45	$1.20	1.05M	prompt-only JSON	Multimodal, also accepts audio
19	thinkingmachines/inkling	$1.00	$4.05	1.05M	prompt-only JSON	Multimodal, also accepts audio

Estimated cost per 1,000 cover picks (assuming about 6 images ≈ 6k prompt tokens + about 200 completion tokens):

Model	Estimated cost per 1,000 picks
qwen/qwen3.7-flash	≈ $0.21
google/gemma-3-4b-it	≈ $0.32
google/gemma-3-12b-it	≈ $0.33
openai/gpt-5-nano	≈ $0.38
amazon/nova-lite-v1	≈ $0.41

OpenCode Zen (free MiMo-V2.5)

OpenCode Zen is the OpenCode team's AI gateway. It is OpenAI-compatible and currently offers MiMo-V2.5 Free (mimo-v2.5-free) at no cost for a limited time. MiMo-V2.5 accepts image input, so it works with FindRomCover.

Setting	Value
Provider	Custom (OpenAI-compatible)
Base URL	https://opencode.ai/zen/v1
API Key	Your Zen key from opencode.ai/auth
Model	mimo-v2.5-free

Notes:

• Free for a limited time; Zen states that data from MiMo-V2.5 Free may be used to improve the model while it is free.
• Zen's model metadata may not report image modality, so the picker's Vision-capable only filter can hide it — uncheck the filter or type the model ID directly.
• Zen also serves paid vision models, for example deepseek-v4-flash-vision-exp ($0.14 / $0.28 per M tokens).
• In OpenCode itself the model is referenced as opencode/mimo-v2.5-free; FindRomCover uses the raw model ID mimo-v2.5-free.

Caveats

• :free variants exist for several models above but are rate-limited and frequently unavailable — use the paid endpoints for batch runs.
• :batch variants are cheaper but asynchronous and do not work with FindRomCover's synchronous client.
• Models without native JSON mode still work: FindRomCover prompts for JSON and parses it from the response text.
• Image token cost is provider-dependent; the estimates above assume about 1,000 tokens per 512px thumbnail.
• Reasoning models may spend output tokens on internal reasoning before producing text. FindRomCover allows up to 4,096 output tokens and reports a clear error if a model still exhausts the budget.

How to use

1. Open Settings > AI Settings....
2. Select OpenRouter and paste your API key.
3. Click Test / Load Models.
4. Type a model ID from the table into the filter box and select it.
5. Save, then use AI Pick Best or Batch Fill.

All models listed here are flagged vision-capable by OpenRouter's modality metadata, so they appear when Vision-capable only is checked.

For OpenCode Zen, choose Provider: Custom (OpenAI-compatible), set the Base URL to https://opencode.ai/zen/v1, paste your Zen key, and enter mimo-v2.5-free as the model.

Choosing a model

Priority	Recommendation
Lowest cost	qwen/qwen3.7-flash
Most reliable JSON output	openai/gpt-5-nano
Best quality per dollar	google/gemma-3-12b-it or google/gemini-2.5-flash-lite
Best Gemma 4 value	google/gemma-4-31b-it
Proven for cover picking	amazon/nova-lite-v1 — very reliable in real batch runs
Free (OpenCode Zen, limited time)	mimo-v2.5-free
No cloud cost	A local model via Ollama, for example qwen2.5vl:7b

Note: Prices change frequently. Verify current pricing on your provider's website before running large batches.

Related pages

• Providers & Models
• AI Settings
• Batch Fill