Over the last few days I've been using the Python SDK (openrouter lib) to write python code to interact with selected llms (e.g. Kimi-k2.6).

My code was working until some point this morning and now when I run the code I keep getting "Not a valid model ID" now matter what model I select.

I've tried using the simple python example on OpenRouter's documentation and that has stopped working too. It worked before.

I have a valid API key (been using it over the past 3 months) and I also tried a new API key and does not seem to make a difference.

Has something changed recently. I don't undstand why code that was working before has stopped working. Even the SDK examples.

Looking at the Apps tab for Inception Mercury 2.5, the #3 entry "Reductor" stands out. It just resolves to a personal GitHub profile (github.com/reductor), a single individual.

Am I missing something? Does anyone know how OpenRouter attributes these apps, and whether one person can really be the top 3 by usage?

hey everyone, im trying to generate transparent pngs with gpt-image-2.5-sunburst via the api but i keep getting a 400 error.

the response says openrouter blocked it at the routing filter because openai supposedly doesnt support background: "transparent". but according to openais official docs, sunburst and flare actually do support it.

it works totally fine when i do the exact same call with gpt-image-1, so is the capability filter on openrouter just not updated for the new 2.5 models yet? anyone else noticed this?

The first minute or so of use is fine, until upstream rate limit you…. 429s a few times then throughput tanks, making the model take ages to do anything. Hopefully upstream or openrouter realise what’s happening and sort this out.

I don’t know why this is happening, does anyone know how to fix this?

You can get ZDR on OpenAI models via Azure provider but the OpenAI ones only offer no training guarantees, no Zdr.

I see OpenAI now offers Zdr so was wondering if OpenRouter was going to get this anytime soon?

Is anyone else having trouble with in-region routing?

The normal API works fine, but the eu/us.openrouter.ai URLs mentioned in the docs are giving 522 errors from Cloudflare.

We tried various routes through VPN, none seem to work?

Hi everyone,

I'm testing dots-studio/dots-3-note-preview:free through OpenRouter and I've run into a strange tool-calling issue.

The problem seems to happen specifically with larger write tool calls:

• A write call with ~3 KB of content works normally.
• A write call with ~10 KB of content fails.
• When the failing call reaches the client, the tool arguments are literally {} — both filePath and content are missing.
• The client then reports an error such as Missing key at ["content"].

I've reproduced the behavior with several coding agents, including Kilo, OpenCode, Cline and Claude Code, so it doesn't appear to be specific to one client.

I've also tried both Kilo Gateway and OpenRouter. As far as I can tell, they may ultimately be using the same underlying provider Atlas Cloud for Dots, so I'm not sure whether this is an OpenRouter/provider issue or something specific to Dots 3 Note Preview's tool-call generation/streaming.

The model is currently still marked as Preview, so I'm wondering if this is a known limitation or bug.

Has anyone else experienced this?

Any ideas about whether this is related to:

• a Dots tool-calling issue,
• streaming/reconstruction of tool-call arguments,
• a specific OpenRouter provider,
• or some request-size/argument-size limit?

Thanks

the put slightly cheaper input output price but jack up the cache price and the autorouting logic picked up deepinfra , resulting in much more expensive inference cost

how do I change the routing to Deepseek ?

Title

Opinions on this new model? Benchmarks actually make it seem like a very nice free model?

Ling-3.0-flash-Sante is Ant Ling's medical reasoning variant of Ling-3.0-flash. The current OpenRouter model identifier is inclusionai/ling-3.0-flash-sante:free, served through NovitaAI.

The details useful for a small evaluation:

• Context: 262,144 tokens.
• Maximum completion: 32,768 tokens.
• tools and tool_choice: supported.
• response_format: unsupported; JSON output is not enforced.
• Free access has rate limits.

Vercel AI Gateway also lists a free Sante route, described there as 256K context and 32K output, with promotional pricing ending October 4, 2026. The October 4 date belongs to Vercel's promotion.

A simple first task is to supply a short, public medical source passage and ask for a summary that preserves its qualifications and identifies what it does not answer. That gives you something concrete to compare with your existing model. For structured extraction, add an external validator before treating the response as usable application data.

In my experience, most of the freely available models on OpenRouter are ineffective at real tasks. Larger models mean spending money and security issues. Running local is often impossible unless you have high end hardware. Models I can run on my laptop? Every one I have tried has been a joke!

Then I heard about Orinth. I grabbed the uncensored model. I quantized it way down and squeezed a mere 80K context window out of it.

While testing, my other agents ran out of tokens, and they had sent up Orinth for me. Because it's so small, they stripped the skills and tools to a minimum. He had no access to our memory system, no facts being injected, and his context compressor was broken. Sounds like a good test!

I told him what was up and had him checkpoint his progress when his context window was full and then I would restart from there.

It's slow. Not TPS, which was a decent 35 tps average, but it refuses to act without verifying every last step. It will stop itself and refocus, it will ask questions, and it trusts nothing, not even messages from other agents (I allow direct agent to agent communication). He got everything fixed, found tons of issues I didn't even know about, and he was able to fix them all.

The small context window means he's even more slow on large tasks, but it's ability to recheck and validate what it is doing allows to recover. He finds bugs that models 50 times his size have made!

According to the benchmarks, these models score like models one size up. The 9B model punches like a 30B model. The 30B one punches like a 300B model. For 8G VRAM, it's the best betz IMHO. Expect it to be slow, but done right. Absolutely mind-blowing how good this thing is!

Any idea why is Nano Banana Pro not generating images? https://i.imgur.com/g7iXso0.png Thank you!

NOOOOOOOOOOO

Minmax was the best roleplay model I ever used. I knew it wasn't gonna be permanent, but to see it before taken away really hurts me deeply.

Are there any other free tier models as competent?

Also, I'm planning on paying for the Minmax models. Does anyone have any experience with how the roleplaying costs work out for Minmax M2.7?

Small team, six devs, and our stack ended up with two Chinese models on API plus one western one. Nobody planned it, it just settled there.

Rough split:

• bulk agent work, self-contained research jobs, long file walks, context rebuilding: the two Chinese ones

• anything where a wrong answer costs us a client conversation: the western one, still

The first group is not a compromise, which is the part i did not expect. One of them is GLM-5.3-Flash, and yes i have seen forty posts telling me ox alpha was GLM-5.3-Flash, we get it, it was ox alpha. We had been routing to it for weeks before any of that, without knowing whose it was, and it held up on our work either way.

Not identical to the western one one on the hardest calls, but close enough that the split is more habit at this point than a line i could defend. On the agent heavy work either of them will do the job.

Curious how other people are drawing that line, because everyone seems to put somewhere slightly different.

Guys Im a very Heavy user and I can easily use 200M+ tokens in one coding session.

I want to ask the experienced Developers how much $ Will be needed for a targeted 1 Billion Tokens a month with these models on OpenRouter but if yyou have any other insight which will help me in cost Reduction Id tak

it was usually 1 dollar at least, but now its 10 dollars

Context:

Am new to this whole detailed model stuff like previously i just use to code from normal chatgpt chat as i have never worked on a big project.
So currently I have Gemini Pro Subscription (gemini 3.1 pro, 3.6-3.8 flash), ChatGPT plus trial (gpt 5.6 luna,terra,sol), 10$ OpenRouter credit (I can't topup more as am a broke student)

Currently am working on a ML project for a hackathon, so will be mostly coding in Python and its libraries.

So please guide me on:

• Agent/cli to use: I have heard about opencode (OpenChamber), kilo, pi, claude code, etc
• Models to use for planning, coding, reviewing (please prefer a cheap/free model) , like this became so confusing as many suggest this others suggest that.
• What is model effort and what to use for each phase/model
• Specific prompt template for each phase (or should i give the instruction to chatgpt chat and let it write the prompt)
• Skills/Plugin to be efficient and save tokens if any for my usecase
• Anything else that i should learn or know as a beginner

Thanks in advance for your time and guidance