r/kiroIDE

It’s been 3 days since Oct started and am already exceeding my 10k credit limit by 7k. Wanted to ask if others are also having this kind of usage or am I a little too excessive in terms of credits?

I run a Kanban-driven multi-agent orchestrator on Hermes Agent: 20+ profiles, 1,000+ skills, MCP routing, and self-hosted Mem0 on pgvector. On Fireworks, I was doing roughly 9-15B tokens a month with a 90-98% cache hit rate, at about 30-60 Kanban tasks a day. I now want to move this to infrastructure I can pay for with my AWS Activate credits, and I've hit some walls.

Constraints

• My only budget is $10k in AWS Activate credits. Anything that can't be paid with them is effectively out of scope for now.
• Bedrock access is gated on my account for both frontier and open-weight models, and I've been told there's no timeline. I'm waiting on AWS Support to initialize my quotas.
• I want one multimodal model that covers all of the orchestration's needs, plus an embedder for Mem0.

What I've looked at so far

• g6e.12xlarge (4x L40S, 192 GB): Qwen3.8-Flash-Next (180B total, 6B active) at Q4, around 114 GB. About $10.49/hr on-demand, or roughly $3.5-6/hr on spot, so $10k lasts ~40 days on-demand or ~2-4 months on spot, running 24/7. FP8 (~186 GB) barely fits, with no room for KV cache.
• g6e.xlarge (1x L40S, 48 GB): Qwen3.8-27B at FP8 (~28 GB), roughly 7 months of credits if run 24/7.
• Embeddings: Qwen3-Embedding-0.6B/4B/8B on the same box, possibly truncated to 1024 dims for pgvector.
• SageMaker endpoints, plain EC2 + vLLM: the same GPUs, but I'd expect the same quota bottleneck. Bedrock Custom Model Import doesn't seem to support these architectures or embedding models.
• Kiro as a Hermes provider (the kiro-acp plugin): interesting because Activate credits can pay for it, but credits are per-task, not per-token, so I can't tell whether it can handle my volume.

Questions

1. Has anyone gotten G/VT quota (48+ vCPUs) approved on a new or Activate account, and how long did it take? Any tips for the request wording?
2. For people serving Flash-Next-class MoE models on 4x L40S: is there a vLLM/SGLang-compatible 4-bit quant (AWQ/GPTQ), and how well did prefix caching hold up with many long-context agents? My cache hit rate on Fireworks was a big part of the economics.
3. Has anyone run Hermes through Kiro (kiro-acp)? How many credits does a multi-step agentic task actually burn, and did you hit rate limits with parallel sessions?
4. Is there any provider or platform that accepts AWS credits for hosted inference of open-weight models and that I haven't listed?
5. Is there a better model than Flash-Next for a single multimodal orchestrator on this budget? I'm open to smaller MoEs if they handle tool calling and long context reliably.
6. Anything else I'm missing on AWS to make $10k last as long as possible (spot strategies, scheduled start/stop, etc.)?

Thanks. Happy to share measurements (throughput, cache hit rate, credits per task) if I get any of this running.