Agnes AI / agnes/agnes-2.5-flash
Agnes 2.5 Flash - access through LLMTR
Agnes 2.5 Flash is Agnes AI's general-purpose model for chat, coding and agent workflows. It has a 524,288-token context window and a single response can be at most 65,536 tokens. It accepts image and video input alongside text, supports tool/function calling (including forced and named tool choice) and schema-enforced JSON output, and streams. Repeated prompt prefixes are served from a prompt cache. The model reasons by default; add the `:fast` suffix when you want a direct answer, or `:think` to force reasoning back on. Reasoning tokens are billed as output. Images and video must be sent as base64 data URLs — this upstream cannot fetch remote URLs, so a public https:// image link is rejected. The model is currently offered free, under a request quota counted over a rolling 24-hour window plus a short-window rate limit; a refused request tells you when to retry.
Technical specifications
| Canonical ID | agnes/agnes-2.5-flash |
|---|---|
| Provider | Agnes AI |
| Context window | 524,288 tokens |
| Operations | CHAT_COMPLETIONS |
| Modalities | text, image, video |
Pricing
An 8% platform margin applies to credit top-ups; model usage prices are not separately marked up.
| Operation | Metric | Unit | Price |
|---|---|---|---|
| CHAT_COMPLETIONS | INPUT_TEXT | PER_1M_TOKENS | Not available |
| CHAT_COMPLETIONS | CACHE_READ | PER_1M_TOKENS | Not available |
| CHAT_COMPLETIONS | OUTPUT_TEXT | PER_1M_TOKENS | Not available |
Example usage
With existing OpenAI SDK flows, change only the base URL and model identifier.
curl https://llmtr.com/v1/chat/completions -H "Authorization: Bearer llmtr-your_key" -H "Content-Type: application/json" -d '{"model":"agnes/agnes-2.5-flash","messages":[{"role":"user","content":"Hello"}]}'Guides about this model
- Atria-Dawn vs Atria-Dawn Preview: stable release or open preview - Both rows are called on LLMTR with the same API key through /v1/chat/completions; they offer a 524,288-token context, text-only input, json_schema and tool calling, and they are free until 31 October 2026, 23:59 (TRT). Atria-Dawn is the stable release; Atria-Dawn Preview is the preview whose weights are open under the MIT license.
- Reasoning and the daily token allowance on Shanghai AI Lab models - All five rows reason before answering by default, and reasoning tokens count toward both max_tokens and the daily token allowance. To turn reasoning off, send "reasoning": false or add :fast to the model id; reasoning_effort returns 400. The rows are free until 31 October 2026, 23:59 (TRT).
- Long-document extraction with Atria-Dawn and JSON Schema - Atria-Dawn can read a long document in one request and return fields that follow a strict JSON Schema, and it is free until 31 October 2026, 23:59 (TRT). Input, output and reasoning share the same context window and the same daily allowance; turning reasoning off for extraction saves tokens.
- Intern-S2 vs Qwen3.8 27B, Nemotron 3.5 Super VL, Agnes 2.5 Flash - All four models read images on LLMTR with the same API key through /v1/chat/completions. Intern-S2 is free until 31 October 2026, 23:59 (TRT) and returns 410 from 1 November 2026; Qwen3.8 27B, Nemotron 3.5 Super VL and Agnes 2.5 Flash run on quotas with no end date set and can be used free of charge after 31 October 2026 as well. Video is open only on Nemotron 3.5 Super VL and Agnes 2.5 Flash; Agnes takes images only as base64 data URLs.
- Shanghai AI Lab models after 1 November 2026: migration guide - The five Shanghai AI Lab models are free until 31 October 2026, 23:59 (TRT); from 1 November 2026, 00:00, they return 410 model_retired and are not redirected. Scientific questions with images and image-reading agents move to Nemotron 3.5 Super VL or Qwen3.6 35B-A3B; long text-based agent work moves to Nemotron 3 Ultra, Agnes 2.5 Flash, DeepSeek V4.1 Flash or MiniMax M3.1 Flash.
- What is Motif 3? The free agentic coding model, measured - What Motif 3 is for, the capabilities measured through LLMTR, the vision claim its own published metadata contradicts, and how it compares with the other free models sharing the same context window.
- Motif 3 API usage: your first request through LLMTR - The steps to call Motif 3 from your existing OpenAI-compatible code, working examples, and which requests spend an allowance on the free row.
- Three silent failures on Motif 3 that still return HTTP 200 - Three concrete cases where an LLM request returns 200 and still fails, the measured behaviour of each, and the defences to add in agent code.
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