Claude Haiku 4.5vsNemotron 3 Super
Claude Haiku 4.5 | Nemotron 3 Super | |
|---|---|---|
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | — | 120B |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | — | 1M |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $1.00 | — |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | $5.00 | — |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | $0.10 | — |
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $1.00Amazon Bedrock | — |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $5.00Amazon Bedrock | — |
| Benchmarks | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 73.3% | 60.5% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 73% | 79.2% |
| BenchmarksPublished by one model only | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 77% | — |
AA Intelligence IndexOverall intelligence — Artificial Analysis composite intelligence index across evals | — | 36 |
| Overview | ||
| Company | Anthropic | NVIDIA |
| Release date | Oct 15 2025 | Mar 11 2026 |
| Access | Proprietary | Open Source |
Other comparisons
Frequently asked questions
Claude Haiku 4.5 and Nemotron 3 Super are evenly matched across the 2 benchmarks they both report (SWE-Bench Verified, GPQA Diamond). Only Claude Haiku 4.5 has a verified first-party API price: $1.00 per million input tokens and $5.00 per million output tokens. No pay-as-you-go API rate is tracked for Nemotron 3 Super. Claude Haiku 4.5 shipped 147 days before Nemotron 3 Super, so benchmark comparisons should account for the intervening progress.
Claude Haiku 4.5 is proprietary, while Nemotron 3 Super is open source.
On SWE-Bench Verified, Claude Haiku 4.5 leads at 73.3% vs Nemotron 3 Super at 60.5%. On GPQA Diamond, Nemotron 3 Super leads at 79.2% vs Claude Haiku 4.5 at 73%.
Claude Haiku 4.5 was released by Anthropic on Oct 15 2025.
Nemotron 3 Super was released by NVIDIA on Mar 11 2026.
Claude Haiku 4.5 leads on SWE-Bench Verified — Claude Haiku 4.5 73.3% vs Nemotron 3 Super 60.5%.
Nemotron 3 Super leads on GPQA Diamond — Claude Haiku 4.5 73% vs Nemotron 3 Super 79.2%.
Only Claude Haiku 4.5 has a verified first-party API price: $1.00 per million input tokens and $5.00 per million output tokens. No pay-as-you-go API rate is tracked for Nemotron 3 Super. Rates are pay-as-you-go API prices verified on August 18, 2026.
Claude Haiku 4.5 is a proprietary model released by Anthropic. Nemotron 3 Super is an open source model released by NVIDIA.