Pick Grok 4 for 256k context with native tool use or real-time data via x integration. 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; Grok 4 if you want a managed API.
Grok 4 (xAI) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Grok 4 is xAI's 2M-context model with live data access and strong reasoning chops. 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 and open vs. closed weights — 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 Grok 4 is API-metered at $3/$15 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 3.9× more — 1M (~1,500 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: NVIDIA Nemotron 3 Super is the newer model by about 8 months (released March 11, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Grok 4
NVIDIA Nemotron 3 Super
Provider
xAI (US)
NVIDIA (US)
Released
July 9, 2025
March 11, 2026
Context window
256K (~384 pages)
1M (~1,500 pages)
Price (in/out)
$3/$15 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
Not published
60.47%
MRCR v2 @ 1M
Not published
Not published
Who wins what
256K context with native tool use: Grok 4 — A core design strength of Grok 4.
Real-time data via X integration: Grok 4 — A core design strength of Grok 4.
Strong academic reasoning: Grok 4 — A core design strength of Grok 4.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B): NVIDIA Nemotron 3 Super — A core design strength of NVIDIA Nemotron 3 Super.
1M-token context with strong long-context retrieval (91.6% RULER @ 1M): NVIDIA Nemotron 3 Super — A core design strength of NVIDIA Nemotron 3 Super.
Strong math reasoning (90.21% AIME 2025): NVIDIA Nemotron 3 Super — A core design strength of NVIDIA Nemotron 3 Super.
Lowest cost at scale: NVIDIA Nemotron 3 Super — At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: NVIDIA Nemotron 3 Super — Its 1M window is about 3.9× larger, 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 Grok 4, 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; Grok 4 is API-only.
Anyone whose priority is 256k context with native tool use: Grok 4 — 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.
Grok 4: where it fits
XAI's 2M-context model with live data access and strong reasoning chops. Released July 9, 2025 by xAI, it is built for 256K context with native tool use, real-time data via X integration, strong academic reasoning, and no long-context surcharge.
Its trade-offs are real: smaller ecosystem than OpenAI/Google, and less independent benchmark coverage. At $3 in / $15 out per million tokens, it sits in the mid 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. Grok 4 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 Grok 4 or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for Grok 4, so the honest test is your own repository — run an identical real bug through both. By design, Grok 4 leans toward 256k context with native tool use while NVIDIA Nemotron 3 Super leans toward high-throughput agentic reasoning (up to 2.2x gpt-oss-120b), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Grok 4 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 Grok 4 is API-metered at $3/$15 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 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4 and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Grok 4, 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, Grok 4 or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super — released March 11, 2026, about 8 months after Grok 4.
Grok 4 vs NVIDIA Nemotron 3 Super
xAI · US | NVIDIA · US · Updated June 2026
Quick verdict
Pick Grok 4 for 256k context with native tool use or real-time data via x integration. 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; Grok 4 if you want a managed API.
Grok 4 (xAI) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Grok 4 is xAI's 2M-context model with live data access and strong reasoning chops. 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 and open vs. closed weights — 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 Grok 4 is API-metered at $3/$15 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 3.9× more — 1M (~1,500 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: NVIDIA Nemotron 3 Super is the newer model by about 8 months (released March 11, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Grok 4
NVIDIA Nemotron 3 Super
Provider
xAI (US)
NVIDIA (US)
Released
July 9, 2025
March 11, 2026
Context window
256K (~384 pages)
1M (~1,500 pages)
Price (in/out)
$3/$15 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
Not published
60.47%
MRCR v2 @ 1M
Not published
Not published
Who wins what
256K context with native tool use
Grok 4
A core design strength of Grok 4.
Real-time data via X integration
Grok 4
A core design strength of Grok 4.
Strong academic reasoning
Grok 4
A core design strength of Grok 4.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B)
NVIDIA Nemotron 3 Super
A core design strength of NVIDIA Nemotron 3 Super.
1M-token context with strong long-context retrieval (91.6% RULER @ 1M)
NVIDIA Nemotron 3 Super
A core design strength of NVIDIA Nemotron 3 Super.
Strong math reasoning (90.21% AIME 2025)
NVIDIA Nemotron 3 Super
A core design strength of NVIDIA Nemotron 3 Super.
Lowest cost at scale
NVIDIA Nemotron 3 Super
At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
NVIDIA Nemotron 3 Super
Its 1M window is about 3.9× larger, 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 Grok 4, 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; Grok 4 is API-only.
Anyone whose priority is 256k context with native tool use
→ Grok 4
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.
Grok 4: where it fits
XAI's 2M-context model with live data access and strong reasoning chops. Released July 9, 2025 by xAI, it is built for 256K context with native tool use, real-time data via X integration, strong academic reasoning, and no long-context surcharge.
Its trade-offs are real: smaller ecosystem than OpenAI/Google, and less independent benchmark coverage. At $3 in / $15 out per million tokens, it sits in the mid 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. Grok 4 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 Grok 4 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 Grok 4 or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for Grok 4, so the honest test is your own repository — run an identical real bug through both. By design, Grok 4 leans toward 256k context with native tool use while NVIDIA Nemotron 3 Super leans toward high-throughput agentic reasoning (up to 2.2x gpt-oss-120b), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Grok 4 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 Grok 4 is API-metered at $3/$15 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 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4 and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Grok 4, 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, Grok 4 or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super — released March 11, 2026, about 8 months after Grok 4.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.