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). FindRomCover's current OpenRouter default is qwen/qwen3.7-flash.
Top 5 cheapest¶
| # | 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 | openai/gpt-5-nano |
$0.05 | $0.40 | 400k | structured outputs + response_format |
Most reliable JSON parsing; smallest GPT-5 variant |
| 3 | google/gemma-3-4b-it |
$0.05 | $0.10 | 131k | structured outputs | Cheapest output tokens; small but genuinely multimodal |
| 4 | google/gemma-3-12b-it |
$0.05 | $0.15 | 131k | structured outputs | Same input price as 4B with better quality |
| 5 | 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 |
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 |
Runner-ups¶
| Model ID | Input $/M | Output $/M | Notes |
|---|---|---|---|
inclusionai/ling-3.0-flash-vl |
$0.06 | $0.18 | Vision-language specialist (124B MoE / 5.5B active) |
qwen/qwen3.5-flash-02-23 |
$0.07 | $0.26 | 1M context |
~z-ai/glm-flash-latest |
$0.07 | $0.25 | 1.3M context |
bytedance-seed/seed-1.6-flash |
$0.07 | $0.30 | 262k context |
google/gemma-3-27b-it |
$0.08 | $0.45 | Larger Gemma 3 |
mistralai/mistral-small-3.2-24b-instruct |
$0.09 | $0.25 | 256k context |
meta-llama/llama-4-scout |
$0.10 | $0.30 | 1.3M context |
google/gemini-2.5-flash-lite |
$0.10 | $0.40 | Known-good quality, per-image pricing |
Free options (testing only)¶
inclusionai/ling-3.0-flash-vl:free, google/gemma-4-31b-it:free, google/gemma-4-26b-a4b-it:free, qwen/qwen3.8-27b:free
OpenRouter's free tier is rate-limited (about 50 requests/day without credits, about 1,000/day after a one-time $10 credit purchase) and can be flaky — fine for trying AI Assist, not for bulk runs.
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 IDmimo-v2.5-free.
Caveats¶
:batchvariants 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¶
- Open
Settings > AI Settings.... - Select OpenRouter and paste your API key.
- Click Test / Load Models.
- Type a model ID from this page into the filter box and select it.
- 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 |
| Proven for cover picking | amazon/nova-lite-v1 — very reliable in real batch runs |
| Free (limited time) | mimo-v2.5-free via OpenCode Zen |
| 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.