Pick GPT-5.6 Terra for balanced everyday work at roughly half of sol's price or competitive with gpt-5.5 quality at about 2x lower cost. 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-5.6 Terra if you want a managed API.
GPT-5.6 Terra (OpenAI) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. GPT-5.6 Terra is the mid-tier daily driver of the GPT-5.6 family — near-flagship quality at about half of Sol's cost. 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 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-5.6 Terra is API-metered at $2.5/$15 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: GPT-5.6 Terra is the newer model by about 4 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-5.6 Terra
NVIDIA Nemotron 3 Super
Provider
OpenAI (US)
NVIDIA (US)
Released
July 9, 2026
March 11, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$2.5/$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
Balanced everyday work at roughly half of Sol's price: GPT-5.6 Terra — A core design strength of GPT-5.6 Terra.
Competitive with GPT-5.5 quality at about 2x lower cost: GPT-5.6 Terra — A core design strength of GPT-5.6 Terra.
Solid agentic coding (Terminal-Bench 2.1 in the mid-80s): GPT-5.6 Terra — A core design strength of GPT-5.6 Terra.
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.
Which should you pick?
A cost-sensitive startup shipping high volume: NVIDIA Nemotron 3 Super — At Open weight (self-host / free) it undercuts GPT-5.6 Terra, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs: NVIDIA Nemotron 3 Super — Open weights let you run it on your own hardware; GPT-5.6 Terra is API-only.
Anyone whose priority is balanced everyday work at roughly half of sol's price: GPT-5.6 Terra — 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-5.6 Terra: where it fits
The mid-tier daily driver of the GPT-5.6 family — near-flagship quality at about half of Sol's cost. Released July 9, 2026 by OpenAI, it is built for balanced everyday work at roughly half of Sol's price, competitive with GPT-5.5 quality at about 2x lower cost, solid agentic coding (Terminal-Bench 2.1 in the mid-80s), and same 1M context and programmatic tool calling as Sol.
Its trade-offs are real: fewer independently verified benchmarks than Sol, and trails it across coding evals, and no open weights. At $2.5 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. GPT-5.6 Terra 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-5.6 Terra or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for GPT-5.6 Terra, so the honest test is your own repository — run an identical real bug through both. By design, GPT-5.6 Terra leans toward balanced everyday work at roughly half of sol's price 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-5.6 Terra 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-5.6 Terra is API-metered at $2.5/$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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-5.6 Terra and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you GPT-5.6 Terra, 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-5.6 Terra or NVIDIA Nemotron 3 Super?
GPT-5.6 Terra — released July 9, 2026, about 4 months after NVIDIA Nemotron 3 Super.
GPT-5.6 Terra vs NVIDIA Nemotron 3 Super
OpenAI · US | NVIDIA · US · Updated June 2026
Quick verdict
Pick GPT-5.6 Terra for balanced everyday work at roughly half of sol's price or competitive with gpt-5.5 quality at about 2x lower cost. 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-5.6 Terra if you want a managed API.
GPT-5.6 Terra (OpenAI) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. GPT-5.6 Terra is the mid-tier daily driver of the GPT-5.6 family — near-flagship quality at about half of Sol's cost. 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 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-5.6 Terra is API-metered at $2.5/$15 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: GPT-5.6 Terra is the newer model by about 4 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-5.6 Terra
NVIDIA Nemotron 3 Super
Provider
OpenAI (US)
NVIDIA (US)
Released
July 9, 2026
March 11, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$2.5/$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
Balanced everyday work at roughly half of Sol's price
GPT-5.6 Terra
A core design strength of GPT-5.6 Terra.
Competitive with GPT-5.5 quality at about 2x lower cost
GPT-5.6 Terra
A core design strength of GPT-5.6 Terra.
Solid agentic coding (Terminal-Bench 2.1 in the mid-80s)
GPT-5.6 Terra
A core design strength of GPT-5.6 Terra.
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.
Which should you pick?
A cost-sensitive startup shipping high volume
→ NVIDIA Nemotron 3 Super
At Open weight (self-host / free) it undercuts GPT-5.6 Terra, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ NVIDIA Nemotron 3 Super
Open weights let you run it on your own hardware; GPT-5.6 Terra is API-only.
Anyone whose priority is balanced everyday work at roughly half of sol's price
→ GPT-5.6 Terra
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-5.6 Terra: where it fits
The mid-tier daily driver of the GPT-5.6 family — near-flagship quality at about half of Sol's cost. Released July 9, 2026 by OpenAI, it is built for balanced everyday work at roughly half of Sol's price, competitive with GPT-5.5 quality at about 2x lower cost, solid agentic coding (Terminal-Bench 2.1 in the mid-80s), and same 1M context and programmatic tool calling as Sol.
Its trade-offs are real: fewer independently verified benchmarks than Sol, and trails it across coding evals, and no open weights. At $2.5 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. GPT-5.6 Terra 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-5.6 Terra 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-5.6 Terra or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for GPT-5.6 Terra, so the honest test is your own repository — run an identical real bug through both. By design, GPT-5.6 Terra leans toward balanced everyday work at roughly half of sol's price 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-5.6 Terra 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-5.6 Terra is API-metered at $2.5/$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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-5.6 Terra and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you GPT-5.6 Terra, 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-5.6 Terra or NVIDIA Nemotron 3 Super?
GPT-5.6 Terra — released July 9, 2026, about 4 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.