Pick Claude Haiku 4.5 for fastest claude model or near-frontier coding for its tier — 73.3% on swe-bench verified. Pick NVIDIA Nemotron 3 Super for high-throughput agentic reasoning (up to 2.2x gpt-oss-120b) or 1m-token context with strong long-context retrieval (91.6% ruler @ 1m). Choose NVIDIA Nemotron 3 Super if you need self-hosting or data privacy; Claude Haiku 4.5 if you want a managed API.
Claude Haiku 4.5 (Anthropic) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Claude Haiku 4.5 is anthropic's fastest, most compact model — built for speed and volume. NVIDIA Nemotron 3 Super is nVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. They diverge most on price, context window, open vs. closed weights and coding benchmarks — each quantified below from the models' real specs.
Key differences
Cost model: NVIDIA Nemotron 3 Super ships open weights you can self-host (hardware cost only, no per-token fee), while Claude Haiku 4.5 is API-metered at $1/$5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: NVIDIA Nemotron 3 Super holds 5× more — 1M (~1,500 pages) vs 200K (~300 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Coding: Claude Haiku 4.5 leads SWE-Bench Verified by 12.8 points (73.3% vs 60.47%) — a real edge on hard, real-world software tasks.
Recency: NVIDIA Nemotron 3 Super is the newer model by about 5 months (released March 11, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Claude Haiku 4.5
NVIDIA Nemotron 3 Super
Provider
Anthropic (US)
NVIDIA (US)
Released
October 15, 2025
March 11, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1/$5 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
73.3%
60.47%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fastest Claude model: Claude Haiku 4.5 — Anthropic's fastest, most compact model — built for speed and volume — and it leads SWE-Bench Verified 73.3% to 60.47%.
Near-frontier coding for its tier — 73.3% on SWE-Bench Verified: Claude Haiku 4.5 — It scores 73.3% on SWE-Bench Verified against NVIDIA Nemotron 3 Super's 60.47% — a 12.8-point edge on real repository work.
Low-latency, high-volume API calls: Claude Haiku 4.5 — Claude Haiku 4.5 lists low-latency, high-volume API calls among its strengths; NVIDIA Nemotron 3 Super does not.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B): NVIDIA Nemotron 3 Super — Claude Haiku 4.5 is comparatively weak here — not for deep reasoning
1M-token context with strong long-context retrieval (91.6% RULER @ 1M): NVIDIA Nemotron 3 Super — Its 1M window holds about 5× more than Claude Haiku 4.5's 200K in a single prompt.
Strong math reasoning (90.21% AIME 2025): NVIDIA Nemotron 3 Super — NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context — and it carries the larger 1M context.
Lowest cost at scale: NVIDIA Nemotron 3 Super — Its weights are open, so at volume you pay for your own hardware instead of Claude Haiku 4.5's $1/$5 per 1M tokens.
Largest single-prompt input: NVIDIA Nemotron 3 Super — Its 1M window is about 5× larger than Claude Haiku 4.5's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: NVIDIA Nemotron 3 Super — At Open weight (self-host / free) it undercuts Claude Haiku 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: NVIDIA Nemotron 3 Super — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: NVIDIA Nemotron 3 Super — Open weights let you run it on your own hardware; Claude Haiku 4.5 is API-only.
Anyone whose priority is fastest claude model: Claude Haiku 4.5 — It is specifically built for that.
Anyone whose priority is high-throughput agentic reasoning (up to 2.2x gpt-oss-120b): NVIDIA Nemotron 3 Super — That is its strongest area.
Claude Haiku 4.5: where it fits
Anthropic's fastest, most compact model — built for speed and volume. Released October 15, 2025 by Anthropic, it is built for fastest Claude model, near-frontier coding for its tier — 73.3% on SWE-Bench Verified, low-latency, high-volume API calls, and cheapest Claude tier at $1/$5.
Its trade-offs are real: smallest context in the family (200K), and not for deep reasoning. At $1 in / $5 out per million tokens, it sits in the budget price band.
NVIDIA Nemotron 3 Super: where it fits
NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. Released March 11, 2026 by NVIDIA, it is built for high-throughput agentic reasoning (up to 2.2x GPT-OSS-120B), 1M-token context with strong long-context retrieval (91.6% RULER @ 1M), strong math reasoning (90.21% AIME 2025), and fully open weights, datasets, and recipes for self-hosting.
Its trade-offs: text-only; no image, audio, or video input, and requires roughly 8x H100-80GB GPUs to self-host at BF16. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
The defining split here is open vs. closed. NVIDIA Nemotron 3 Super gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Claude Haiku 4.5 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is Claude Haiku 4.5 or NVIDIA Nemotron 3 Super better for coding?
On SWE-Bench Verified, Claude Haiku 4.5 scores 73.3% and NVIDIA Nemotron 3 Super scores 60.47% — Claude Haiku 4.5 has the measurable edge.
Which is cheaper, Claude Haiku 4.5 or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Haiku 4.5 is API-metered at $1/$5 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
NVIDIA Nemotron 3 Super — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Haiku 4.5 and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Claude Haiku 4.5, NVIDIA Nemotron 3 Super and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Claude Haiku 4.5 or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super — released March 11, 2026, about 5 months after Claude Haiku 4.5.
Claude Haiku 4.5 vs NVIDIA Nemotron 3 Super
Anthropic · US | NVIDIA · US · Updated June 2026
Quick verdict
Pick Claude Haiku 4.5 for fastest claude model or near-frontier coding for its tier — 73.3% on swe-bench verified. Pick NVIDIA Nemotron 3 Super for high-throughput agentic reasoning (up to 2.2x gpt-oss-120b) or 1m-token context with strong long-context retrieval (91.6% ruler @ 1m). Choose NVIDIA Nemotron 3 Super if you need self-hosting or data privacy; Claude Haiku 4.5 if you want a managed API.
Claude Haiku 4.5 (Anthropic) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Claude Haiku 4.5 is anthropic's fastest, most compact model — built for speed and volume. NVIDIA Nemotron 3 Super is nVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. They diverge most on price, context window, open vs. closed weights and coding benchmarks — each quantified below from the models' real specs.
Key differences at a glance
▸Cost model: NVIDIA Nemotron 3 Super ships open weights you can self-host (hardware cost only, no per-token fee), while Claude Haiku 4.5 is API-metered at $1/$5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: NVIDIA Nemotron 3 Super holds 5× more — 1M (~1,500 pages) vs 200K (~300 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Coding: Claude Haiku 4.5 leads SWE-Bench Verified by 12.8 points (73.3% vs 60.47%) — a real edge on hard, real-world software tasks.
▸Recency: NVIDIA Nemotron 3 Super is the newer model by about 5 months (released March 11, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Claude Haiku 4.5
NVIDIA Nemotron 3 Super
Provider
Anthropic (US)
NVIDIA (US)
Released
October 15, 2025
March 11, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1/$5 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
73.3%
60.47%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fastest Claude model
Claude Haiku 4.5
Anthropic's fastest, most compact model — built for speed and volume — and it leads SWE-Bench Verified 73.3% to 60.47%.
Near-frontier coding for its tier — 73.3% on SWE-Bench Verified
Claude Haiku 4.5
It scores 73.3% on SWE-Bench Verified against NVIDIA Nemotron 3 Super's 60.47% — a 12.8-point edge on real repository work.
Low-latency, high-volume API calls
Claude Haiku 4.5
Claude Haiku 4.5 lists low-latency, high-volume API calls among its strengths; NVIDIA Nemotron 3 Super does not.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B)
NVIDIA Nemotron 3 Super
Claude Haiku 4.5 is comparatively weak here — not for deep reasoning
1M-token context with strong long-context retrieval (91.6% RULER @ 1M)
NVIDIA Nemotron 3 Super
Its 1M window holds about 5× more than Claude Haiku 4.5's 200K in a single prompt.
Strong math reasoning (90.21% AIME 2025)
NVIDIA Nemotron 3 Super
NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context — and it carries the larger 1M context.
Lowest cost at scale
NVIDIA Nemotron 3 Super
Its weights are open, so at volume you pay for your own hardware instead of Claude Haiku 4.5's $1/$5 per 1M tokens.
Largest single-prompt input
NVIDIA Nemotron 3 Super
Its 1M window is about 5× larger than Claude Haiku 4.5's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ NVIDIA Nemotron 3 Super
At Open weight (self-host / free) it undercuts Claude Haiku 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ NVIDIA Nemotron 3 Super
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ NVIDIA Nemotron 3 Super
Open weights let you run it on your own hardware; Claude Haiku 4.5 is API-only.
Anyone whose priority is fastest claude model
→ Claude Haiku 4.5
It is specifically built for that.
Anyone whose priority is high-throughput agentic reasoning (up to 2.2x gpt-oss-120b)
→ NVIDIA Nemotron 3 Super
That is its strongest area.
Claude Haiku 4.5: where it fits
Anthropic's fastest, most compact model — built for speed and volume. Released October 15, 2025 by Anthropic, it is built for fastest Claude model, near-frontier coding for its tier — 73.3% on SWE-Bench Verified, low-latency, high-volume API calls, and cheapest Claude tier at $1/$5.
Its trade-offs are real: smallest context in the family (200K), and not for deep reasoning. At $1 in / $5 out per million tokens, it sits in the budget price band.
NVIDIA Nemotron 3 Super: where it fits
NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. Released March 11, 2026 by NVIDIA, it is built for high-throughput agentic reasoning (up to 2.2x GPT-OSS-120B), 1M-token context with strong long-context retrieval (91.6% RULER @ 1M), strong math reasoning (90.21% AIME 2025), and fully open weights, datasets, and recipes for self-hosting.
Its trade-offs: text-only; no image, audio, or video input, and requires roughly 8x H100-80GB GPUs to self-host at BF16. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
The defining split here is open vs. closed. NVIDIA Nemotron 3 Super gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Claude Haiku 4.5 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both Claude Haiku 4.5 and NVIDIA Nemotron 3 Super without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
Is Claude Haiku 4.5 or NVIDIA Nemotron 3 Super better for coding?
On SWE-Bench Verified, Claude Haiku 4.5 scores 73.3% and NVIDIA Nemotron 3 Super scores 60.47% — Claude Haiku 4.5 has the measurable edge.
Which is cheaper, Claude Haiku 4.5 or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Haiku 4.5 is API-metered at $1/$5 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
NVIDIA Nemotron 3 Super — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Haiku 4.5 and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Claude Haiku 4.5, NVIDIA Nemotron 3 Super and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Claude Haiku 4.5 or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super — released March 11, 2026, about 5 months after Claude Haiku 4.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.