Pick GPT-6 Astra for computer & browser use (screenspot-pro 92.7%) or cybersecurity exploit development (exploitbench 100%). 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; GPT-6 Astra if you want a managed API.
GPT-6 Astra (OpenAI) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. GPT-6 Astra is openAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks. 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 GPT-6 Astra is API-metered at $10/$50 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: 1.05M tokens vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: GPT-6 Astra is the newer model by about 6 months (released September 3, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-6 Astra
NVIDIA Nemotron 3 Super
Provider
OpenAI (US)
NVIDIA (US)
Released
September 3, 2026
March 11, 2026
Context window
1.05M tokens (~1,575 pages)
1M (~1,500 pages)
Price (in/out)
$10/$50 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
60.47%
MRCR v2 @ 1M
96.3%
Not published
Who wins what
Computer & browser use (ScreenSpot-Pro 92.7%): GPT-6 Astra — OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks — and it is the newer of the two.
Cybersecurity exploit development (ExploitBench 100%): GPT-6 Astra — GPT-6 Astra lists cybersecurity exploit development (ExploitBench 100%) among its strengths; NVIDIA Nemotron 3 Super does not.
Frontier math reasoning (FrontierMath Tier 4: 97.6%): GPT-6 Astra — GPT-6 Astra lists frontier math reasoning (FrontierMath Tier 4: 97.6%) among its strengths; NVIDIA Nemotron 3 Super does not.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B): 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 its weights are open while GPT-6 Astra is API-only.
1M-token context with strong long-context retrieval (91.6% RULER @ 1M): NVIDIA Nemotron 3 Super — GPT-6 Astra is comparatively weak here — pricing doubles for prompts over 272K tokens (input/cache 2x, output 1.5x)
Strong math reasoning (90.21% AIME 2025): NVIDIA Nemotron 3 Super — NVIDIA Nemotron 3 Super lists strong math reasoning (90.21% AIME 2025) among its strengths; GPT-6 Astra does not.
Lowest cost at scale: NVIDIA Nemotron 3 Super — Its weights are open, so at volume you pay for your own hardware instead of GPT-6 Astra's $10/$50 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: NVIDIA Nemotron 3 Super — At Open weight (self-host / free) it undercuts GPT-6 Astra, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-6 Astra — Larger 1.05M tokens 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; GPT-6 Astra is API-only.
Anyone whose priority is computer & browser use (screenspot-pro 92.7%): GPT-6 Astra — 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.
GPT-6 Astra: where it fits
OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks. Released September 3, 2026 by OpenAI, it is built for computer & browser use (ScreenSpot-Pro 92.7%), cybersecurity exploit development (ExploitBench 100%), frontier math reasoning (FrontierMath Tier 4: 97.6%), and long-context recall (MRCR v2 512K-1M: 96.3%).
Its trade-offs are real: no native audio or video input, pricing doubles for prompts over 272K tokens (input/cache 2x, output 1.5x), trails Meta's Muse Spark 1.3 on some coding evals (DeepSWE v1.1: 74.1 vs 75.4), and a separate opt-in "Daybreak" program gives vetted cybersecurity defenders a less-restricted version for legitimate vulnerability research; the public version already refuses ~91.5% of offensive cyber jailbreak attempts by default. At $10 in / $50 out per million tokens, it sits in the premium 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. GPT-6 Astra 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 GPT-6 Astra or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for GPT-6 Astra, so the honest test is your own repository — run an identical real bug through both. By design, GPT-6 Astra leans toward computer & browser use (screenspot-pro 92.7%) 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, GPT-6 Astra 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 GPT-6 Astra is API-metered at $10/$50 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?
Effectively neither — 1.05M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-6 Astra and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Astra, 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, GPT-6 Astra or NVIDIA Nemotron 3 Super?
GPT-6 Astra — released September 3, 2026, about 6 months after NVIDIA Nemotron 3 Super.
GPT-6 Astra vs NVIDIA Nemotron 3 Super
OpenAI · US | NVIDIA · US · Updated June 2026
Quick verdict
Pick GPT-6 Astra for computer & browser use (screenspot-pro 92.7%) or cybersecurity exploit development (exploitbench 100%). 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; GPT-6 Astra if you want a managed API.
GPT-6 Astra (OpenAI) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. GPT-6 Astra is openAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks. 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 GPT-6 Astra is API-metered at $10/$50 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: 1.05M tokens vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: GPT-6 Astra is the newer model by about 6 months (released September 3, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-6 Astra
NVIDIA Nemotron 3 Super
Provider
OpenAI (US)
NVIDIA (US)
Released
September 3, 2026
March 11, 2026
Context window
1.05M tokens (~1,575 pages)
1M (~1,500 pages)
Price (in/out)
$10/$50 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
60.47%
MRCR v2 @ 1M
96.3%
Not published
Who wins what
Computer & browser use (ScreenSpot-Pro 92.7%)
GPT-6 Astra
OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks — and it is the newer of the two.
Cybersecurity exploit development (ExploitBench 100%)
GPT-6 Astra
GPT-6 Astra lists cybersecurity exploit development (ExploitBench 100%) among its strengths; NVIDIA Nemotron 3 Super does not.
Frontier math reasoning (FrontierMath Tier 4: 97.6%)
GPT-6 Astra
GPT-6 Astra lists frontier math reasoning (FrontierMath Tier 4: 97.6%) among its strengths; NVIDIA Nemotron 3 Super does not.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B)
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 its weights are open while GPT-6 Astra is API-only.
1M-token context with strong long-context retrieval (91.6% RULER @ 1M)
NVIDIA Nemotron 3 Super
GPT-6 Astra is comparatively weak here — pricing doubles for prompts over 272K tokens (input/cache 2x, output 1.5x)
Strong math reasoning (90.21% AIME 2025)
NVIDIA Nemotron 3 Super
NVIDIA Nemotron 3 Super lists strong math reasoning (90.21% AIME 2025) among its strengths; GPT-6 Astra does not.
Lowest cost at scale
NVIDIA Nemotron 3 Super
Its weights are open, so at volume you pay for your own hardware instead of GPT-6 Astra's $10/$50 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ NVIDIA Nemotron 3 Super
At Open weight (self-host / free) it undercuts GPT-6 Astra, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-6 Astra
Larger 1.05M tokens 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; GPT-6 Astra is API-only.
Anyone whose priority is computer & browser use (screenspot-pro 92.7%)
→ GPT-6 Astra
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.
GPT-6 Astra: where it fits
OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks. Released September 3, 2026 by OpenAI, it is built for computer & browser use (ScreenSpot-Pro 92.7%), cybersecurity exploit development (ExploitBench 100%), frontier math reasoning (FrontierMath Tier 4: 97.6%), and long-context recall (MRCR v2 512K-1M: 96.3%).
Its trade-offs are real: no native audio or video input, pricing doubles for prompts over 272K tokens (input/cache 2x, output 1.5x), trails Meta's Muse Spark 1.3 on some coding evals (DeepSWE v1.1: 74.1 vs 75.4), and a separate opt-in "Daybreak" program gives vetted cybersecurity defenders a less-restricted version for legitimate vulnerability research; the public version already refuses ~91.5% of offensive cyber jailbreak attempts by default. At $10 in / $50 out per million tokens, it sits in the premium 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. GPT-6 Astra 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 GPT-6 Astra 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 GPT-6 Astra or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for GPT-6 Astra, so the honest test is your own repository — run an identical real bug through both. By design, GPT-6 Astra leans toward computer & browser use (screenspot-pro 92.7%) 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, GPT-6 Astra 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 GPT-6 Astra is API-metered at $10/$50 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?
Effectively neither — 1.05M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-6 Astra and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Astra, 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, GPT-6 Astra or NVIDIA Nemotron 3 Super?
GPT-6 Astra — released September 3, 2026, about 6 months after NVIDIA Nemotron 3 Super.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.