Intelligence
24.3
24
General reasoning and benchmark headroom.
LimitedNVIDIA: Nemotron 3 Nano 30B A3B is a budget text-first model from nvidia with a fast runtime profile, large context posture, and the clearest fit around long-context research / multimodal.
Benchmark blend
Dev workflow signal
Large
Budget tier
NVIDIA: Nemotron 3 Nano 30B A3B currently reads as a budget text-first option with large context and a fast runtime profile.
Decision Strip
Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.
General reasoning and benchmark headroom.
LimitedTTFT 0.53s
Above averageHow much prompt and task state can stay in view.
Above average$0.24 output / 1M
EfficientEditorial Profile
Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.
NVIDIA Nemotron 3 Nano 30B A3B is a small language MoE model with highest compute efficiency and accuracy for developers to build specialized agentic AI systems. The model is fully open with open-weights, datasets and recipes so developers can easily customize, optimize, and deploy the model on their infrastructure for maximum privacy and security.
nvidia text-first profile
Long-context research / Multimodal with large context and fast runtime.
Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.
Large context headroom supports repo-wide prompts and long research sessions.
Latency and throughput look responsive enough for interactive loops.
Budget-friendly input pricing is a strength, but raw capability may vary by workload.
Current metadata points to a text-first profile rather than a broad multimodal one.
Long-context summarization, repo analysis, and policy or document review.
Benchmarks
Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.
Broad reasoning, knowledge depth, and flagship benchmark posture.
Software implementation, debugging quality, and coding benchmark signal.
Formal reasoning, structured problem solving, and competition-style math.
Long-horizon execution quality and interactive benchmark evidence.
Specs & Pricing
Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.
This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.
Metadata
Verification details remain available, but the page no longer forces them ahead of the editorial read.