Pick Grok 4.5 for cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost or extreme token efficiency — around 4x fewer output tokens per task than opus 4.8. 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).
Grok 4.5 (xAI, 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. Grok 4.5 is xAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex. 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
Context window: Qwen 3.8-Max holds 2.1× more — 1M (~1,573 pages) vs 500K (~750 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Qwen 3.8-Max is the newer model by about 26 days (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
Grok 4.5
Qwen 3.8-Max
Provider
xAI (US)
Alibaba (China)
Released
July 8, 2026
August 3, 2026
Context window
500K (~750 pages)
1M (~1,573 pages)
Price (in/out)
$2/$6 per 1M tokens
$2/$6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheap, token-efficient agentic coding — about GPT-5.5-Codex quality at roughly half the cost: Grok 4.5 — 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
Extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8: Grok 4.5 — Grok 4.5 lists extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8 among its strengths; Qwen 3.8-Max does not.
In-IDE coding, trained on real Cursor developer sessions and shipped natively in Cursor: Grok 4.5 — 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 — Grok 4.5 is comparatively weak here — smaller 500K context (halved from the 1M generation), with pricing that doubles above 200K tokens
Large 1M-token context with multimodal input (text, image, video): Qwen 3.8-Max — Its 1M window holds about 2.1× more than Grok 4.5's 500K in a single prompt.
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 carries the larger 1M context.
Largest single-prompt input: Qwen 3.8-Max — Its 1M window is about 2.1× larger than Grok 4.5's 500K, fitting roughly 1,573 pages in one prompt.
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 cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost: Grok 4.5 — 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: Grok 4.5 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.
Grok 4.5: where it fits
XAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex. Released July 8, 2026 by xAI, it is built for cheap, token-efficient agentic coding — about GPT-5.5-Codex quality at roughly half the cost, extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8, in-IDE coding, trained on real Cursor developer sessions and shipped natively in Cursor, and top-tier placement on the Artificial Analysis Intelligence Index.
Its trade-offs are real: smaller 500K context (halved from the 1M generation), with pricing that doubles above 200K tokens, and eU launch delayed; no open weights. At $2 in / $6 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." Grok 4.5 (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.
Frequently asked questions
Is Grok 4.5 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, Grok 4.5 leans toward cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost 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, Grok 4.5 or Qwen 3.8-Max?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Qwen 3.8-Max — 1M vs 500K, about 2.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4.5 and Qwen 3.8-Max together?
Yes — a multi-model platform like LumiChats gives you Grok 4.5, 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, Grok 4.5 or Qwen 3.8-Max?
Qwen 3.8-Max — released August 3, 2026, about 26 days after Grok 4.5.
Grok 4.5 vs Qwen 3.8-Max
xAI · US | Alibaba · China · Updated June 2026
Quick verdict
Pick Grok 4.5 for cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost or extreme token efficiency — around 4x fewer output tokens per task than opus 4.8. 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).
Grok 4.5 (xAI, 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. Grok 4.5 is xAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex. 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
▸Context window: Qwen 3.8-Max holds 2.1× more — 1M (~1,573 pages) vs 500K (~750 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Qwen 3.8-Max is the newer model by about 26 days (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
Grok 4.5
Qwen 3.8-Max
Provider
xAI (US)
Alibaba (China)
Released
July 8, 2026
August 3, 2026
Context window
500K (~750 pages)
1M (~1,573 pages)
Price (in/out)
$2/$6 per 1M tokens
$2/$6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheap, token-efficient agentic coding — about GPT-5.5-Codex quality at roughly half the cost
Grok 4.5
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
Extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8
Grok 4.5
Grok 4.5 lists extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8 among its strengths; Qwen 3.8-Max does not.
In-IDE coding, trained on real Cursor developer sessions and shipped natively in Cursor
Grok 4.5
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
Grok 4.5 is comparatively weak here — smaller 500K context (halved from the 1M generation), with pricing that doubles above 200K tokens
Large 1M-token context with multimodal input (text, image, video)
Qwen 3.8-Max
Its 1M window holds about 2.1× more than Grok 4.5's 500K in a single prompt.
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 carries the larger 1M context.
Largest single-prompt input
Qwen 3.8-Max
Its 1M window is about 2.1× larger than Grok 4.5's 500K, fitting roughly 1,573 pages in one prompt.
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 cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost
→ Grok 4.5
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
→ Grok 4.5 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.
Grok 4.5: where it fits
XAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex. Released July 8, 2026 by xAI, it is built for cheap, token-efficient agentic coding — about GPT-5.5-Codex quality at roughly half the cost, extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8, in-IDE coding, trained on real Cursor developer sessions and shipped natively in Cursor, and top-tier placement on the Artificial Analysis Intelligence Index.
Its trade-offs are real: smaller 500K context (halved from the 1M generation), with pricing that doubles above 200K tokens, and eU launch delayed; no open weights. At $2 in / $6 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." Grok 4.5 (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 Grok 4.5 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.
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, Grok 4.5 leans toward cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost 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, Grok 4.5 or Qwen 3.8-Max?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Qwen 3.8-Max — 1M vs 500K, about 2.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4.5 and Qwen 3.8-Max together?
Yes — a multi-model platform like LumiChats gives you Grok 4.5, 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, Grok 4.5 or Qwen 3.8-Max?
Qwen 3.8-Max — released August 3, 2026, about 26 days after Grok 4.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.