nemotron-lightning-3.5-30b-a3bFireworks AI
- api
- chat
- hosting
- US
- model lab
- NVIDIA
- weights
- open
- added
- August 2026
- model id
- fireworks/nemotron-lightning-3.5-30b-a3b
capabilities 4/8
- input
- $0.05
- output
- $0.20
- cache write
- -
- cache read
- $0.01
worked cost
| volume | cost |
|---|---|
| 100K in + 10K out | $0.0070 |
| 1M in + 100K out | $0.0700 |
| 10M in + 1M out | $0.70 |
Requesty charges what the upstream provider charges, with no markup and no per-request fee. Prompt caching and smart routing cut the effective cost further on repeated context. Gateway pricing
no measured traffic for this endpoint yet. pricing above is the provider's own
no published scores for this exact variant. region deployments and highspeed tiers usually share the base model's results
- retention
- none
- trains on prompts
- no
- hosted in
- US
Terms are the provider's, not Requesty's: routing a request here puts it under them. Fireworks Privacy Policy
Need every request to stay in one jurisdiction? EU hosting routes only through EU-hosted providers.
fireworks/nemotron-lightning-3.5-30b-a3bthis id pins the fireworks ai deployment, with no routing and no failover. the managed id on the canonical page routes across all 1 providers instead
from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create( model="fireworks/nemotron-lightning-3.5-30b-a3b", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ],) print(response.choices[0].message.content)
Change the base url to https://router.requesty.ai/v1, use your Requesty key, set the model to the id above. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog. Browse all models
Nemotron-Lightning-3.5-30B-A3B is a 30B-parameter Mixture-of-Experts language model (3B active) from NVIDIA's Nemotron-H family, built on a hybrid Mamba-Transformer architecture for efficient long-context inference. Like other models in the family, it responds to queries by first generating a reasoning trace and then concluding with a final response, with reasoning behavior configurable through a flag in the chat template. It includes a multi-token prediction (MTP) speculative decoding head for low-latency serving.
questions 5
How much does nemotron-lightning-3.5-30b-a3b cost?
What is the context window of nemotron-lightning-3.5-30b-a3b?
What can nemotron-lightning-3.5-30b-a3b do?
How do I use nemotron-lightning-3.5-30b-a3b with the OpenAI SDK?
Can I run nemotron-lightning-3.5-30b-a3b through Requesty?
more from fireworks ai 8
| endpoint | ctx | in /M |
|---|---|---|
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| muse-glimmer-30b | 131K | $0.35 |
| qwen3.8-max | 1M | $2.00 |
| deepseek-v4-flash-0731 | 1M | $0.22 |
call nemotron-lightning-3.5-30b-a3b through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover when a provider degrades, and prompt caching built in. Methodology