Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Haiku 4.5
58
Nemotron 3 Nano Omni 30B A3B
56
Pick Claude Haiku 4.5 if you want the stronger benchmark profile. Nemotron 3 Nano Omni 30B A3B only becomes the better choice if you want the cheaper token bill or you need the larger 256K context window.
Coding
+19.8 difference
Claude Haiku 4.5
Nemotron 3 Nano Omni 30B A3B
$1 / $5
$0 / $0
N/A
N/A
N/A
N/A
200K
256K
Pick Claude Haiku 4.5 if you want the stronger benchmark profile. Nemotron 3 Nano Omni 30B A3B only becomes the better choice if you want the cheaper token bill or you need the larger 256K context window.
Claude Haiku 4.5 has the cleaner provisional overall profile here, landing at 58 versus 56. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Claude Haiku 4.5's sharpest advantage is in coding, where it averages 73.3 against 53.5.
Claude Haiku 4.5 is also the more expensive model on tokens at $1.00 input / $5.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Nemotron 3 Nano Omni 30B A3B. That is roughly Infinityx on output cost alone. Nemotron 3 Nano Omni 30B A3B is the reasoning model in the pair, while Claude Haiku 4.5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Nemotron 3 Nano Omni 30B A3B gives you the larger context window at 256K, compared with 200K for Claude Haiku 4.5.
Claude Haiku 4.5 is ahead on BenchLM's provisional leaderboard, 58 to 56.
Claude Haiku 4.5 has the edge for coding in this comparison, averaging 73.3 versus 53.5. Nemotron 3 Nano Omni 30B A3B stays close enough that the answer can still flip depending on your workload.
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