Pick NVIDIA Nemotron 3 Ultra for the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48) or fast, efficient long-horizon agentic reasoning via a hybrid mamba-transformer design. Pick Qwen 3.8-Max for near-frontier quality at value pricing — artificial analysis intelligence index 58 or large 1m-token context with multimodal input (text, image, video). Choose NVIDIA Nemotron 3 Ultra if you need self-hosting or data privacy; Qwen 3.8-Max if you want a managed API.
NVIDIA Nemotron 3 Ultra (NVIDIA, US) and Qwen 3.8-Max (Alibaba, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. NVIDIA Nemotron 3 Ultra is nVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. Qwen 3.8-Max is alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. 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 Ultra ships open weights you can self-host (hardware cost only, no per-token fee), while Qwen 3.8-Max is API-metered at $2/$6 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: 1M 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: Qwen 3.8-Max is the newer model by about 2 months (released August 3, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
NVIDIA Nemotron 3 Ultra
Qwen 3.8-Max
Provider
NVIDIA (US)
Alibaba (China)
Released
June 4, 2026
August 3, 2026
Context window
1M (~1,500 pages)
1M (~1,573 pages)
Price (in/out)
Open weight (self-host / free)
$2/$6 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
The most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48): NVIDIA Nemotron 3 Ultra — Open weights make this possible at all — Qwen 3.8-Max is API-only, so it cannot leave the vendor's servers.
Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design: NVIDIA Nemotron 3 Ultra — Qwen 3.8-Max is comparatively weak here — flashier coding/agentic benchmarks (e.g. Terminal-Bench 86.6) are Alibaba's own, not independently reproduced
A fully open release — weights, training data, and recipes under a permissive license: NVIDIA Nemotron 3 Ultra — Qwen 3.8-Max is comparatively weak here — open weights were announced for release but had not shipped as of mid-August 2026 — a closed API for now
Near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58: Qwen 3.8-Max — NVIDIA Nemotron 3 Ultra is comparatively weak here — trails the best Chinese open models on overall intelligence
Large 1M-token context with multimodal input (text, image, video): Qwen 3.8-Max — NVIDIA Nemotron 3 Ultra is comparatively weak here — a 550B mixture-of-experts is heavy to self-host, and the 1M context is rarely served in full
Mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token: Qwen 3.8-Max — Alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped — and it is the newer of the two.
Lowest cost at scale: NVIDIA Nemotron 3 Ultra — Its weights are open, so at volume you pay for your own hardware instead of Qwen 3.8-Max's $2/$6 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: NVIDIA Nemotron 3 Ultra — At Open weight (self-host / free) it undercuts Qwen 3.8-Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Qwen 3.8-Max — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: NVIDIA Nemotron 3 Ultra — Open weights let you run it on your own hardware; Qwen 3.8-Max is API-only.
Anyone whose priority is the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48): NVIDIA Nemotron 3 Ultra — It is specifically built for that.
Anyone whose priority is near-frontier quality at value pricing — artificial analysis intelligence index 58: Qwen 3.8-Max — That is its strongest area.
An enterprise with regional data-residency rules: NVIDIA Nemotron 3 Ultra or Qwen 3.8-Max — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
NVIDIA Nemotron 3 Ultra: where it fits
NVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. Released June 4, 2026 by NVIDIA, it is built for the most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48), fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design, a fully open release — weights, training data, and recipes under a permissive license, and strong coding for an open model (SWE-Bench Verified in the high 60s).
Its trade-offs are real: trails the best Chinese open models on overall intelligence, and a 550B mixture-of-experts is heavy to self-host, and the 1M context is rarely served in full. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
Qwen 3.8-Max: where it fits
Alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. Released August 3, 2026 by Alibaba, it is built for near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58, large 1M-token context with multimodal input (text, image, video), mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token, and $2/$6 per million tokens — far below US flagships like Claude Opus 5 and GPT-5.6 Sol.
Its trade-offs: open weights were announced for release but had not shipped as of mid-August 2026 — a closed API for now, active-parameter count is not officially disclosed by Alibaba, flashier coding/agentic benchmarks (e.g. Terminal-Bench 86.6) are Alibaba's own, not independently reproduced, and trails the very top models (Opus 5, Fable 5, GPT-5.6 Sol) on independent tests. At $2 in / $6 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. NVIDIA Nemotron 3 Ultra gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Qwen 3.8-Max 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 NVIDIA Nemotron 3 Ultra or Qwen 3.8-Max better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, NVIDIA Nemotron 3 Ultra leans toward the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48) while Qwen 3.8-Max leans toward near-frontier quality at value pricing — artificial analysis intelligence index 58, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, NVIDIA Nemotron 3 Ultra or Qwen 3.8-Max?
NVIDIA Nemotron 3 Ultra is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Qwen 3.8-Max is API-metered at $2/$6 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 — 1M vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both NVIDIA Nemotron 3 Ultra and Qwen 3.8-Max together?
Yes — a multi-model platform like LumiChats gives you NVIDIA Nemotron 3 Ultra, Qwen 3.8-Max 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, NVIDIA Nemotron 3 Ultra or Qwen 3.8-Max?
Qwen 3.8-Max — released August 3, 2026, about 2 months after NVIDIA Nemotron 3 Ultra.
NVIDIA Nemotron 3 Ultra vs Qwen 3.8-Max
NVIDIA · US | Alibaba · China · Updated June 2026
Quick verdict
Pick NVIDIA Nemotron 3 Ultra for the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48) or fast, efficient long-horizon agentic reasoning via a hybrid mamba-transformer design. Pick Qwen 3.8-Max for near-frontier quality at value pricing — artificial analysis intelligence index 58 or large 1m-token context with multimodal input (text, image, video). Choose NVIDIA Nemotron 3 Ultra if you need self-hosting or data privacy; Qwen 3.8-Max if you want a managed API.
NVIDIA Nemotron 3 Ultra (NVIDIA, US) and Qwen 3.8-Max (Alibaba, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. NVIDIA Nemotron 3 Ultra is nVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. Qwen 3.8-Max is alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. 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 Ultra ships open weights you can self-host (hardware cost only, no per-token fee), while Qwen 3.8-Max is API-metered at $2/$6 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: 1M 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: Qwen 3.8-Max is the newer model by about 2 months (released August 3, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
NVIDIA Nemotron 3 Ultra
Qwen 3.8-Max
Provider
NVIDIA (US)
Alibaba (China)
Released
June 4, 2026
August 3, 2026
Context window
1M (~1,500 pages)
1M (~1,573 pages)
Price (in/out)
Open weight (self-host / free)
$2/$6 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
The most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48)
NVIDIA Nemotron 3 Ultra
Open weights make this possible at all — Qwen 3.8-Max is API-only, so it cannot leave the vendor's servers.
Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design
NVIDIA Nemotron 3 Ultra
Qwen 3.8-Max is comparatively weak here — flashier coding/agentic benchmarks (e.g. Terminal-Bench 86.6) are Alibaba's own, not independently reproduced
A fully open release — weights, training data, and recipes under a permissive license
NVIDIA Nemotron 3 Ultra
Qwen 3.8-Max is comparatively weak here — open weights were announced for release but had not shipped as of mid-August 2026 — a closed API for now
Near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58
Qwen 3.8-Max
NVIDIA Nemotron 3 Ultra is comparatively weak here — trails the best Chinese open models on overall intelligence
Large 1M-token context with multimodal input (text, image, video)
Qwen 3.8-Max
NVIDIA Nemotron 3 Ultra is comparatively weak here — a 550B mixture-of-experts is heavy to self-host, and the 1M context is rarely served in full
Mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token
Qwen 3.8-Max
Alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped — and it is the newer of the two.
Lowest cost at scale
NVIDIA Nemotron 3 Ultra
Its weights are open, so at volume you pay for your own hardware instead of Qwen 3.8-Max's $2/$6 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ NVIDIA Nemotron 3 Ultra
At Open weight (self-host / free) it undercuts Qwen 3.8-Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Qwen 3.8-Max
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ NVIDIA Nemotron 3 Ultra
Open weights let you run it on your own hardware; Qwen 3.8-Max is API-only.
Anyone whose priority is the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48)
→ NVIDIA Nemotron 3 Ultra
It is specifically built for that.
Anyone whose priority is near-frontier quality at value pricing — artificial analysis intelligence index 58
→ Qwen 3.8-Max
That is its strongest area.
An enterprise with regional data-residency rules
→ NVIDIA Nemotron 3 Ultra or Qwen 3.8-Max
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
NVIDIA Nemotron 3 Ultra: where it fits
NVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. Released June 4, 2026 by NVIDIA, it is built for the most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48), fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design, a fully open release — weights, training data, and recipes under a permissive license, and strong coding for an open model (SWE-Bench Verified in the high 60s).
Its trade-offs are real: trails the best Chinese open models on overall intelligence, and a 550B mixture-of-experts is heavy to self-host, and the 1M context is rarely served in full. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
Qwen 3.8-Max: where it fits
Alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. Released August 3, 2026 by Alibaba, it is built for near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58, large 1M-token context with multimodal input (text, image, video), mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token, and $2/$6 per million tokens — far below US flagships like Claude Opus 5 and GPT-5.6 Sol.
Its trade-offs: open weights were announced for release but had not shipped as of mid-August 2026 — a closed API for now, active-parameter count is not officially disclosed by Alibaba, flashier coding/agentic benchmarks (e.g. Terminal-Bench 86.6) are Alibaba's own, not independently reproduced, and trails the very top models (Opus 5, Fable 5, GPT-5.6 Sol) on independent tests. At $2 in / $6 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. NVIDIA Nemotron 3 Ultra gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Qwen 3.8-Max 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 NVIDIA Nemotron 3 Ultra and Qwen 3.8-Max 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 NVIDIA Nemotron 3 Ultra or Qwen 3.8-Max better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, NVIDIA Nemotron 3 Ultra leans toward the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48) while Qwen 3.8-Max leans toward near-frontier quality at value pricing — artificial analysis intelligence index 58, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, NVIDIA Nemotron 3 Ultra or Qwen 3.8-Max?
NVIDIA Nemotron 3 Ultra is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Qwen 3.8-Max is API-metered at $2/$6 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 — 1M vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both NVIDIA Nemotron 3 Ultra and Qwen 3.8-Max together?
Yes — a multi-model platform like LumiChats gives you NVIDIA Nemotron 3 Ultra, Qwen 3.8-Max 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, NVIDIA Nemotron 3 Ultra or Qwen 3.8-Max?
Qwen 3.8-Max — released August 3, 2026, about 2 months after NVIDIA Nemotron 3 Ultra.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.