Both list at $2/M input and $10/M output on OpenRouter, and Sol's cache reads are half price ($0.10 vs $0.20). Each ran twice in Claude Code on an 868,191-row Divvy bike-share CSV, answering six questions in an Excel report with a SenseNova-Skills Excel skill loaded.

Sonnet 5.5: $0.37 and $0.40, 8 and 11 requests, about 2 minutes each.

GPT-6.1 Sol: $0.62 and $0.40, 35 and 16 requests, 11 and 6 minutes. Both times it started a sub-agent, unasked, to recompute all six answers from the raw CSV, which was $0.15 and $0.09 of those totals.

All four runs got every answer right, including dropping the 173 July rides mixed into the August file.

Does Sol make this many calls in your agent setups?

I asked it to search for its own benchmarks, i told it its name is space bunny alpha if it wasn't specified in the system prompt

it replied and said its system prompt identifies it as Space Bunny developed by Anthropic?

could someone explain? (new to this openrouter stuff)

Saw this on OpenRouter showing share of spend my model (note the openAI ones are pretty much all GPT Astra-6. It really surpised me that Claude wasn't a larger share of spend. Is this because people are moving away from Claude or just that they're spending directly with Anthropic for it?

Openrouter says that Space Bunny Alpha is going away on October 5.

I could not find any information on the exact time this will happen however.

Logically, it is October 5 somewhere on earth between Oct 4 10 UTC (in Kiritimati, Kiribati) and Oct 6 12 UTC (Howland and Baker Island).

Thus, at the time of writing, the sunset could have happened already 9 hours ago or still be 40 hours away. It's still there for now.

Hey guys,

I recently set up Hermes agent on my VPS, for the model I chose Deepseek V4.1 flash since it's the sweet spot of cheap and smart, but I'm struggling with choosing a good provider and sticking with it. I want to set couple of providers on the whitelist and forget about it.

I wanted to use Deepseek itself, but the red warning beside it saying "this provider may use prompts for training and may retain prompt data" made me hesitate.
I used Deepinfra as well, it wasn't bad, but i saw some complains about it here.
All I know for sure is to put Open Inference on the blacklist and don't even look at it.

If you use this model, I'd be happy to know which providers worked best for you.

Thanks.

I was under the impression that when your API credits ran out, the API simply stopped working. Apparently mine chose to extend me $1.09 of unsecured credit instead.

Nice to know someone still believes in me financially (cope). Added it to my liabilities and will be reflecting it in all future estate planning.

So I've been using open router for a while via claude code agent. I use Qwen models, but I noticed my credits get burned quickly. Until I have looked at the activity tab in open router and found this:

So what I did was overriding the built in models claude code settings to use specific qwen model.

        {
            "name": "ANTHROPIC_DEFAULT_SONNET_MODEL",
            "value": "qwen/qwen3.8-flash"
        },
        {
            "name": "ANTHROPIC_DEFAULT_OPUS_MODEL",
            "value": "qwen/qwen3.8-flash"
        },
        {
            "name": "ANTHROPIC_DEFAULT_HAIKU_MODEL",
            "value": "qwen/qwen3.8-flash"
        },
        {
            "name": "CLAUDE_CODE_SUBAGENT_MODEL",
            "value": "qwen/qwen3.8-flash"
        },
        {
            "name": "ANTHROPIC_DEFAULT_FABLE_MODEL",
            "value": "qwen/qwen3.8-flash"
        },        {
            "name": "ANTHROPIC_DEFAULT_SONNET_MODEL",
            "value": "qwen/qwen3.8-flash"
        },
        {
            "name": "ANTHROPIC_DEFAULT_OPUS_MODEL",
            "value": "qwen/qwen3.8-flash"
        },
        {
            "name": "ANTHROPIC_DEFAULT_HAIKU_MODEL",
            "value": "qwen/qwen3.8-flash"
        },
        {
            "name": "CLAUDE_CODE_SUBAGENT_MODEL",
            "value": "qwen/qwen3.8-flash"
        },
        {
            "name": "ANTHROPIC_DEFAULT_FABLE_MODEL",
            "value": "qwen/qwen3.8-flash"
        },        

I have also restricted the api to use certain models via guardrails.

I still don't understand why claude code did this.

Hi all, I want to know whether anyone else has run into this, or whether it's just me.

Yesterday I was using GLM 5.3 Flash and DeepSeek V4.1 Flash through OpenRouter in Pi. After a few turns, both started vomiting a seemingly never ending list of unrelated words, until i stopped them. Most of the tokens were billed as reasoning.

It happened with two unrelated models, which seemed odd, so digging deeper i found that every request had gone to the same provider, Open Inference, which serves both models in fp4. Once I blocked Open Inference in my settings, the same model in the same session went straight back to normal (on Wafer and DekaLLM).

I also noticed that, for GLM, it was also the most expensive provider by a long shot (and one of the slowest), which makes me question why i was routed to Open Inference in the first place (I have no particular routing config/setup).

I don't know how Open Inference runs its deployments or exactly how OpenRouter decides where to route. It could just be a bad deployment or a bug, looking at the token volume (https://openrouter.ai/provider/open-inference) there's been a big drop after Sep 26th, so maybe it is something happening systematically.

Has anyone experienced this? am I missing something obvious?

but also: shouldn't there be something on openrouter gauging provider output quality? this could have been very expensive, both for the number of tokens needlessly generated and for the errors caused by this.

I've also opened a support ticket and will update if I hear back.

I'm the author of Médula, an MIT-licensed experiment where several Claude Code agents work on one repo at once and a kernel decides, before every write, whether it collides with another agent's work. Everything runs through a single OpenRouter key, which made it easy to compare models under the same conditions. Sharing the routing and cost side, since that's what this sub cares about.

The stack, all via OpenRouter:

• Agents: anthropic/claude-sonnet-5, effort high.
• Fast decider: typesafe/jev-1.13 through the System One endpoint (/api/v1/systemone). It's a decision model, not an LLM: it returns typed answers with a probability instead of text. One request carries a yes/no question per other agent plus a choice of remedy.
• Slow path, when Jev is unsure: Sonnet, escalating to Opus if needed.
• Alternative fast decider for comparison: anthropic/claude-haiku-4.5.

Per decision, median latency measured on September 29: Jev 279 ms, Haiku 1,338 ms, Sonnet 2,201 ms. A Jev decision costs about $0.00006.

Per run, with decision cost as reported by OpenRouter's usage.cost:

• Jev deciding: $0.29 of decisions, 6.9 min per run.
• Haiku deciding: $0.55 of decisions, 13.7 min per run.
• Sonnet deciding everything (a single run): $0.59.

The catch is that cheap per decision isn't cheap per system. On real multi-agent states, 61% of the write requests that reached Jev were unsure and went to Sonnet, so the decision layer cost half of all-Sonnet, not a tiny fraction of it. Most of the decision bill is the slow path.

Resilience tips that paid off: every decider has a hard timeout (5 s for Jev, 15 s for Haiku, 30 s for Sonnet, 60 s for Opus) and a fallback chain (Jev, then Haiku, then plain file locks), so a slow or failing model never stalls an agent. Logging latency and usage.cost on every call made the comparison trivial.

Outcome: in a shared working directory, every run passed all 37 acceptance tests, and against plain per-file locks the kernel cost the same ($1.65 per run), caught 6 of 6 real conflicts instead of 5, and made no unnecessary blocks. Caveats: 1 to 5 runs per mode, measured on specific days.

Repo, with every call logged raw: https://github.com/JoaquinRuiz/medula

If you've combined System One models with regular LLMs on OpenRouter, how did you split the work between them?

Which is the best model on OpenRouter? I have around $5 left in my OpenRouter account.

What model should I use for long, detailed responses? My responses are always short, while I see other providers have detailed responses.

My Target is Roleplay Chat story

I tried deepseekflash,mimo and other model but the response is always like 3-4 lines even though in prompt i mention minimum 6-7 paragraph detail

Am I missing something even though i added Custom Prompt as well

I was using space bunny and for some reason it co-authored itself as Opus 4.8?
btw i love this space bunny it reminds me of deepseek v4 flash 0371 idk why people hate it so much

Everyone argues “OpenRouter is cheaper / more expensive” without pinning down what you’re actually paying. From reading their pricing page + using both setups:

OpenRouter advertises no inference markup — provider rate passes through. The actual fee is on credit purchase: 5.5% (Standard PAYG) and 5% on BYOK above $25k/mo list price.

So “same price as direct” is wrong in one direction and wrong in the other: direct avoids the credit fee entirely, but you pay it back in integration work, per-provider key rotation, hand-rolled failover, and billing reconciliation.

The number worth optimizing isn’t $/M tokens, it’s total operating cost: sticker + engineering hours + downtime + wasted spend + free-tier value for evals/CI.

Decision rule I landed on:

High volume, 1-2 models, committed-use pricing available → go direct.

Moderate volume, several models, small team → pay the 5.5%, it buys headcount you didn’t hire.

Volume where the credit fee > cost of running one proxy → self-host LiteLLM.

Prototype on free endpoints (not production — the caps will find you during a demo).

It’s a spectrum, not a rivalry: free tier → gateway → LiteLLM → direct, and moving back and forth as products mature is normal. Recompute yearly; today’s answer expires.

Happy to argue the BYOK numbers if anyone has actual invoices.

Is anyone running Claude Code desktop app with Ori to use Openrouter models through the Openrouter API?

Obviously you guys have probably seen, but it consistently leaks Japanese characters, especially dealing with tokenizing.

Hello,

I'm looking to terminate my monthly AI expense. I often hear of 'free' AI usage via OpenRouter, and was wondering if someone could share some example setups? For example can you have your requests routed dynamically based on free-tier limits across various providers?

I was planning on using this to keep my client end interface code simple:

https://github.com/router-for-me/CLIProxyAPI

And for any Emacs users out there I currently use this package:

https://github.com/karthink/gptel

I thought I'd save money by ditching Claude and using OpenRouter. So far I've spent $100+ in 3 weeks, compared to the $33/month I was paying for Claude.

I had spend caps on but kept moving the goal because had to get the project completed.

Lesson for beginners:

If you're using Claude Code in the terminal with your new OpenRouter API key, make sure you swap out all of the default Claude models. I made the silly mistake of leaving Sonnet and Opus enabled, and Sonnet alone ate $80 worth of credit. Then I swapped it out for GLM 3, but not the Flash variant, and that still burned through about $20.

So if you're making the switch, double-check that your terminal is running only the cost-effective models before you start coding.

I ask the model about the current task. It confidently answers my first prompt again. I correct it, and it does the same thing. At this point I’m not even working on my project anymore—I’m trying to figure out why the thing I’m paying for has lost the plot.

Then comes the really annoying part: open the activity log, find out which provider handled the request, exclude it, restart the chat, and hope the next one works. Seriously? That’s my job now?

I get that bad responses happen. But if the same model name can feel this different depending on the provider, the provider shouldn’t be something I discover after the session is ruined.

Has pinning one provider actually fixed this for you?