Gemini 4 Carbon vs Qwen 3.8-Max

Google · US  |  Alibaba · China · Updated June 2026

Quick verdict

Pick Gemini 4 Carbon for ranked first on the artificial analysis intelligence index v5.0 with 59 at launch (artificial analysis now shows 60) or google-reported 88.2% on sec-bench pro and 54.8% on exploitgym for vulnerability discovery and exploit validation. 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).

Gemini 4 Carbon (Google, 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. Gemini 4 Carbon is google's October 28, 2026 limited release for cyber defenders - top of the Artificial Analysis index at launch, priced at $2/$10 introductory, with no public API date yet. 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. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.

Key differences at a glance

Side-by-side specs

SpecGemini 4 CarbonQwen 3.8-Max
ProviderGoogle (US) Alibaba (China)
ReleasedOctober 28, 2026 August 3, 2026
Context window1M tokens (~1,500 pages) 1M (~1,573 pages)
Price (in/out)$2/$10 per 1M tokens $2/$6 per 1M tokens
Open weight?No — API only No — API only
Modalitiestext, image, audio, video, code text, image, video, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Ranked first on the Artificial Analysis Intelligence Index v5.0 with 59 at launch (Artificial Analysis now shows 60)

Gemini 4 Carbon

Google's October 28, 2026 limited release for cyber defenders - top of the Artificial Analysis index at launch, priced at $2/$10 introductory, with no public API date yet — and it is the newer of the two.

Google-reported 88.2% on SEC-bench Pro and 54.8% on ExploitGym for vulnerability discovery and exploit validation

Gemini 4 Carbon

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

Google-reported 71.0% on CWE-bench for patching

Gemini 4 Carbon

Gemini 4 Carbon lists google-reported 71.0% on CWE-bench for patching among its strengths; Qwen 3.8-Max does not.

Near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58

Qwen 3.8-Max

Gemini 4 Carbon is comparatively weak here — introductory pricing rises to $4/$20 afterward, and Google has not said when that happens

Large 1M-token context with multimodal input (text, image, video)

Qwen 3.8-Max

Gemini 4 Carbon is comparatively weak here — google has not published context or modality specs - the 1M window and modalities shown come from Artificial Analysis and Vals

Mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token

Qwen 3.8-Max

Qwen 3.8-Max lists mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token among its strengths; Gemini 4 Carbon does not.

Which should you pick?

Someone analysing very long documents or codebases

→ Qwen 3.8-Max

Larger 1M window fits more in one prompt.

Anyone whose priority is ranked first on the artificial analysis intelligence index v5.0 with 59 at launch (artificial analysis now shows 60)

→ Gemini 4 Carbon

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

→ Gemini 4 Carbon 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.

Gemini 4 Carbon: where it fits

Google's October 28, 2026 limited release for cyber defenders - top of the Artificial Analysis index at launch, priced at $2/$10 introductory, with no public API date yet. Released October 28, 2026 by Google, it is built for ranked first on the Artificial Analysis Intelligence Index v5.0 with 59 at launch (Artificial Analysis now shows 60), google-reported 88.2% on SEC-bench Pro and 54.8% on ExploitGym for vulnerability discovery and exploit validation, google-reported 71.0% on CWE-bench for patching, and introductory $2/$10 per million tokens, matching Gemini 4 Argon, with cached input 95% off.

Its trade-offs are real: limited release: rolling out to a subset of cyber defenders, then trusted partners via the Fairwind Program, with no date for developers or consumers, no public API model listing yet, so most users cannot call it today, introductory pricing rises to $4/$20 afterward, and Google has not said when that happens, and google has not published context or modality specs - the 1M window and modalities shown come from Artificial Analysis and Vals. At $2 in / $10 out per million tokens, it sits in the mid price band.

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

This is less "which is smarter" and more "which ecosystem fits." Gemini 4 Carbon (US) and Qwen 3.8-Max (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.

Want both Gemini 4 Carbon 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.

See pricing

Frequently asked questions

Is Gemini 4 Carbon 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, Gemini 4 Carbon leans toward ranked first on the artificial analysis intelligence index v5.0 with 59 at launch (artificial analysis now shows 60) 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, Gemini 4 Carbon or Qwen 3.8-Max?

They are priced almost identically, so cost will not decide between them.

Which has the bigger context window?

Effectively neither — 1M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Gemini 4 Carbon and Qwen 3.8-Max together?

Yes — a multi-model platform like LumiChats gives you Gemini 4 Carbon, 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, Gemini 4 Carbon or Qwen 3.8-Max?

Gemini 4 Carbon — released October 28, 2026, about 3 months after Qwen 3.8-Max.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.