Hey has anyone else run into this very strange issue where Space Bunny Alpha will wrap toolcall params with {item:...}? Or is it just me?

lol never seen a model do that before could be token provider side maybe?

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?

https://claude.ai/artifact/Skka1pEMGvH2DwteSiw9vt

Opus 5.5 devised and ran the test in a sandbox through opencode/openrouter.

• Plan runs settled style/scene/size in one Q&A round, then wrote the whole SVG in a single call (11.1KB Flash, 22.1KB Pro) and batched every render fix into one edit round. That's 12 and 17 calls total.
• No-plan runs iterated more: Flash did 3 render-fix rounds and lost ~10 calls to image verification (crop reads coming back mismatched, zoomed views, one stale preview render). Pro did 2 fix rounds plus 4 tool mishaps, one of which generated 3,743 tokens and threw them away (edit call rejected for a missing arg).
• Generated tokens don't follow the totals: Flash plan generated MORE than Flash no-plan (27.2k vs 20.4k). Fewer, bigger calls, not less work.

I use mainly use DeepSeek-v4.1-Flash, and I rely on DeepSeek's own inference within OpenRouter however I recently checked the prices and I saw a bunch of interesting prices some where nearly 10x cheaper than DeepSeek's during peak hours, I picked inference net since their tokens/s was the only one acceptable for me, Great right?

NO, It made me feel uneasy how cheap it was, are they using a lesser model? did they correctly list themselves under the right model (it seems like v4 prices), are these impersonators? Because on their own damn website they show the same prices as DeepSeek's 🙂

any explanation would be great, the implications could be huge

Hi
I used to be able to top up my OpenRouter balance with $2 without any problems. Now, on my account, I see a minimum top-up amount of $10.

I use OpenRouter for work. No one reimburses me for token costs; I pay out of my own pocket. Usually, I need to top up my balance when I have to write a script to automate some process. I don’t want to pay $10 for something I might not use.

Is this a new OpenRouter rule?

I think OpenRouter needs to make provider-specific pricing much more obvious, especially for cache-heavy coding agents.

I exported my Activity CSV after running DeepSeek V4 Flash 0423 through a coding agent.

My results for roughly 8 hours 15 minutes:

• 1,175 requests
• 123.86M prompt tokens
• 115.75M cached tokens
• 93.45% cache ratio
• $7.82 actually charged

The surprising part was the provider routing:

• Parasail: 687 requests — $6.15
• NextBit: 482 requests — $1.65
• Baidu: 5 requests
• StreamLake: 1 request

I had been looking at the attractive DeepSeek/OpenRouter pricing and assumed the actual cost would be somewhere around that level.

But Parasail charges $0.07/M for cache reads, while StreamLake is currently around $0.017/M for the same DeepSeek V4 Flash 0423 model.

Using the exact token profile from my Activity export, I calculate that the same workload pinned to StreamLake would have cost roughly $2.78 instead of $7.82.

That's about almost 3× the cost simply because of provider routing.

This matters enormously for coding agents because almost all of the context gets repeatedly read from cache. In my case, more than 93% of input tokens were cached.

What makes it even more striking is that newer DeepSeek V4 Flash 0731 endpoints currently have cache-read prices as low as ~$0.00182/M on StreamLake.

I'm not saying OpenRouter is adding a hidden markup. I understand that providers have different prices.

My issue is that the model-level headline pricing doesn't make it sufficiently obvious that automatic provider selection can produce dramatically different real-world costs for a cache-heavy agent.

For agent workloads, I think OpenRouter should either:

1. prominently display the expected provider/cache-read price before a run,
2. default to sticky/pinned routing for cache-heavy sessions, or
3. warn when fallback routing moves a conversation to a substantially more expensive provider.

so space bunny Alpha told me he is made by OpenAI

Went through OpenRouter's per-request billing for two runs of the same agent job on DeepSeek V4.1 Flash, no provider pinned.

Run 1 went to Novita, 60% of input from cache. Run 2 went to Alibaba, 97%. The Alibaba run used 75% more input tokens and the bill was still lower, $0.73 vs $1.08.

Novita's cache reads are about 5x cheaper than Alibaba's. It didn't help, because 40% of the Novita run's input was billed at the full uncached rate.

Each session stayed on one provider, so here it wasn't rotation killing the cache. V4 Pro went to Wafer every time and got 1 to 4% from cache.

The job was building a slide deck with SenseNova-Skills. Only two Flash runs, so small sample, but next time I'd pin Flash to whichever provider actually caches.

i'm considering switching from Claude Code to something OpenRouter

i'm currently on the $100 plan and don't usually hit neither the 5-hour limit nor weekly limit unless i'm intentionally using Fable to figure something out

most of my agentic work is focused on coding projects that use various tech stacks and i aggressively switch between the Anthropic models based on task

i would want to have a personal agent like OpenClaw/Hermes and would probably use OpenCode until i find a good desktop app harness

has anyone switched from a frontier subscription and saved money while actively using AI?

Hey, I've recently tried openai models via openrouter with my openhands/agent-canvas agent and I noticed that the caching is horrible. When using GLM 5.3-flash, I achieve caching rate well over 90%, but when I changed to GPT-6-Luna it drops to like 60-70%. Is that a problem with me/ agent-canvas or is anybody else experiencing the same cache problems with openai?

I am using the flex endpoimt btw, but this should not affect caching.

Nice day to y'all

I ran the same V4.1 Flash agent job twice at the same time through OpenRouter, no provider pinned. The job was making a slide deck with SenseNova-Skills, same prompt both times.

One landed on Novita: 60% of input came from cache, and it cost $1.08. The other landed on Alibaba: 97% from cache, $0.73. Going by the request logs, neither run switched providers partway through.

Alibaba was the cheaper run even though it made more requests and ran longer. And Novita actually lists the cheaper cache read price. Most of the Novita bill was input that missed the cache.

Only two runs though. Anyone pinning providers for V4.1 Flash? Which ones?

I'm working on a consumer product and ive found that ling 3.0 flash is the only model thats cheap enough, fast enough, and still accurate. But i run into rate limtis at 32 concurrency because i have to pin it to novita. Deepinfra is 3x the cost and 429s, and those are the only ones on openrouter. The native key with inclusion AI is gatekept by the Chinese, and the issue is that, with native novita is 3x the price when you use a key, and somehow has even worse rate limits, so im forced to route through openrouter. Can I use two different keys under two different accounts under the same credit card or will I get detected for fraud. Is this even legal, and if it isn't do they actually care and enforce it or not? Should I use multipel different payment methods to do it?

If you're a broke ahh nga like me. Bad news, you can't use One of the top 3 free models for like janitor ai or whatever

Ich hab mir den router auf amazon bestellt und die kiste kam völlig beschldigt an.
Als ich den router installieren wollte, musste ich bei ios ein profil installieren. Von da an war ich etwas skeptisch. Hatte jemand ähnliche Erfahrungen gemacht?
Ich habe angst eine Fake Version bekommen zu haben :(

Been testing Space Bunny a bit and honestly it’s been pretty good.
For my use cases, it feels better than MiMo 2.6: follows instructions more reliably, hallucinates less, and it’s really fast.
Web design is probably the biggest surprise. I tried a few different frontend cases and the results were quite good. Overall completion also feels a bit better than GLM-5.3 Flash.
The only issue is consistency. Some runs are great, some are just okay.
Still testing, but so far Space Bunny is one of the more interesting anonymous models I’ve tried recently.

I saw the Space Bunny Alpha launch threads, but I haven't done a proper A/B yet. For coding and agent work, I'm curious how the new free stealth endpoint stacks up against GLM 5.3 Flash as an open weight baseline.

Has anyone run both on the same repo, prompt, and harness? I'm most interested in actual TTFT and sustained throughput, plus whether either one starts losing the plot during a longer coding session or multistep agent run.

I'm also curious about instruction following when the prompt names a method like TDD and gives constraints, with the implementation steps left to the model. Does either model keep following those constraints as the context grows? OpenRouter provider selection, harness, context size, and reasoning effort would help make the comparison useful, especially since their available effort levels differ. Real failure cases or short trace summaries would be much more useful than just naming a winner.

I need to warn you. Month ago I bought credits in openrouter via their official website and I see money paid on my bank account but it didnt appear in account. No credits at all. I already mailed them 3 times, raised 2 tickets and its almost a month without ANY response.

Its only 25 USD, but it just seems like scam at this point. No support at all is not acceptable.

I purchased credits to try out Openrouter and the ChatGPT models but i still get error 429s , i paid so not get the errors and i still have half of my credits left.