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 Qwen3.6 27B for the best open coding score in its family — 77.2% on swe-bench verified, beating alibaba's own 397b mixture-of-experts at a fifteenth of the size or dense, so quality per gigabyte of vram is high: it fits one consumer gpu when quantised. Choose Qwen3.6 27B if you need self-hosting or data privacy; Grok 4.5 if you want a managed API.
Grok 4.5 (xAI, US) and Qwen3.6 27B (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. Qwen3.6 27B is a dense 27B multimodal model with its family's best coding score — it beats a 397B mixture-of-experts, but costs more per token. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Qwen3.6 27B ships open weights you can self-host (hardware cost only, no per-token fee), while Grok 4.5 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: Grok 4.5 holds 1.9× more — 500K (~750 pages) vs 256K (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Grok 4.5 is the newer model by about 3 months (released July 8, 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
Qwen3.6 27B
Provider
xAI (US)
Alibaba (China)
Released
July 8, 2026
April 22, 2026
Context window
500K (~750 pages)
256K (~393 pages)
Price (in/out)
$2/$6 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
77.2%
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 — Its 500K window holds about 1.9× more than Qwen3.6 27B's 256K in a single prompt.
Extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8: Grok 4.5 — Qwen3.6 27B is comparatively weak here — every parameter fires on every token, so it is slower and costlier per token than the sparse 35B
In-IDE coding, trained on real Cursor developer sessions and shipped natively in Cursor: Grok 4.5 — XAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex — and it carries the larger 500K context.
The best open coding score in its family — 77.2% on SWE-Bench Verified, beating Alibaba's own 397B mixture-of-experts at a fifteenth of the size: Qwen3.6 27B — Open weights make this possible at all — Grok 4.5 is API-only, so it cannot leave the vendor's servers.
Dense, so quality per gigabyte of VRAM is high: it fits one consumer GPU when quantised: Qwen3.6 27B — A dense 27B multimodal model with its family's best coding score — it beats a 397B mixture-of-experts, but costs more per token — and its weights are open while Grok 4.5 is API-only.
Far stronger agentic work than its sparse sibling (59.3 against 51.5 on Terminal-Bench 2.0): Qwen3.6 27B — Qwen3.6 27B lists far stronger agentic work than its sparse sibling (59.3 against 51.5 on Terminal-Bench 2.0) among its strengths; Grok 4.5 does not.
Lowest cost at scale: Qwen3.6 27B — Its weights are open, so at volume you pay for your own hardware instead of Grok 4.5's $2/$6 per 1M tokens.
Largest single-prompt input: Grok 4.5 — Its 500K window is about 1.9× larger than Qwen3.6 27B's 256K, fitting roughly 750 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Qwen3.6 27B — At Open weight (self-host / free) it undercuts Grok 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Grok 4.5 — Larger 500K window fits more in one prompt.
A team with data-privacy or self-hosting needs: Qwen3.6 27B — Open weights let you run it on your own hardware; Grok 4.5 is API-only.
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 the best open coding score in its family — 77.2% on swe-bench verified, beating alibaba's own 397b mixture-of-experts at a fifteenth of the size: Qwen3.6 27B — That is its strongest area.
An enterprise with regional data-residency rules: Grok 4.5 or Qwen3.6 27B — 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.
Qwen3.6 27B: where it fits
A dense 27B multimodal model with its family's best coding score — it beats a 397B mixture-of-experts, but costs more per token. Released April 22, 2026 by Alibaba, it is built for the best open coding score in its family — 77.2% on SWE-Bench Verified, beating Alibaba's own 397B mixture-of-experts at a fifteenth of the size, dense, so quality per gigabyte of VRAM is high: it fits one consumer GPU when quantised, far stronger agentic work than its sparse sibling (59.3 against 51.5 on Terminal-Bench 2.0), and dense models fine-tune far more predictably than mixture-of-experts models do.
Its trade-offs: every parameter fires on every token, so it is slower and costlier per token than the sparse 35B, hosted output pricing is the harshest in its family, and provider input prices moved by roughly half in a single quarter, and its SWE-Bench score comes from Alibaba's internal scaffold rather than the standard public harness. 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. Qwen3.6 27B gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Grok 4.5 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 Grok 4.5 or Qwen3.6 27B better for coding?
Public SWE-Bench figures are not available for Grok 4.5, 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 Qwen3.6 27B leans toward the best open coding score in its family — 77.2% on swe-bench verified, beating alibaba's own 397b mixture-of-experts at a fifteenth of the size, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Grok 4.5 or Qwen3.6 27B?
Qwen3.6 27B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Grok 4.5 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?
Grok 4.5 — 500K vs 256K, about 1.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4.5 and Qwen3.6 27B together?
Yes — a multi-model platform like LumiChats gives you Grok 4.5, Qwen3.6 27B 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 Qwen3.6 27B?
Grok 4.5 — released July 8, 2026, about 3 months after Qwen3.6 27B.
Grok 4.5 vs Qwen3.6 27B
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 Qwen3.6 27B for the best open coding score in its family — 77.2% on swe-bench verified, beating alibaba's own 397b mixture-of-experts at a fifteenth of the size or dense, so quality per gigabyte of vram is high: it fits one consumer gpu when quantised. Choose Qwen3.6 27B if you need self-hosting or data privacy; Grok 4.5 if you want a managed API.
Grok 4.5 (xAI, US) and Qwen3.6 27B (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. Qwen3.6 27B is a dense 27B multimodal model with its family's best coding score — it beats a 397B mixture-of-experts, but costs more per token. 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: Qwen3.6 27B ships open weights you can self-host (hardware cost only, no per-token fee), while Grok 4.5 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: Grok 4.5 holds 1.9× more — 500K (~750 pages) vs 256K (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Grok 4.5 is the newer model by about 3 months (released July 8, 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
Qwen3.6 27B
Provider
xAI (US)
Alibaba (China)
Released
July 8, 2026
April 22, 2026
Context window
500K (~750 pages)
256K (~393 pages)
Price (in/out)
$2/$6 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
77.2%
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
Its 500K window holds about 1.9× more than Qwen3.6 27B's 256K in a single prompt.
Extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8
Grok 4.5
Qwen3.6 27B is comparatively weak here — every parameter fires on every token, so it is slower and costlier per token than the sparse 35B
In-IDE coding, trained on real Cursor developer sessions and shipped natively in Cursor
Grok 4.5
XAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex — and it carries the larger 500K context.
The best open coding score in its family — 77.2% on SWE-Bench Verified, beating Alibaba's own 397B mixture-of-experts at a fifteenth of the size
Qwen3.6 27B
Open weights make this possible at all — Grok 4.5 is API-only, so it cannot leave the vendor's servers.
Dense, so quality per gigabyte of VRAM is high: it fits one consumer GPU when quantised
Qwen3.6 27B
A dense 27B multimodal model with its family's best coding score — it beats a 397B mixture-of-experts, but costs more per token — and its weights are open while Grok 4.5 is API-only.
Far stronger agentic work than its sparse sibling (59.3 against 51.5 on Terminal-Bench 2.0)
Qwen3.6 27B
Qwen3.6 27B lists far stronger agentic work than its sparse sibling (59.3 against 51.5 on Terminal-Bench 2.0) among its strengths; Grok 4.5 does not.
Lowest cost at scale
Qwen3.6 27B
Its weights are open, so at volume you pay for your own hardware instead of Grok 4.5's $2/$6 per 1M tokens.
Largest single-prompt input
Grok 4.5
Its 500K window is about 1.9× larger than Qwen3.6 27B's 256K, fitting roughly 750 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen3.6 27B
At Open weight (self-host / free) it undercuts Grok 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Grok 4.5
Larger 500K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Qwen3.6 27B
Open weights let you run it on your own hardware; Grok 4.5 is API-only.
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 the best open coding score in its family — 77.2% on swe-bench verified, beating alibaba's own 397b mixture-of-experts at a fifteenth of the size
→ Qwen3.6 27B
That is its strongest area.
An enterprise with regional data-residency rules
→ Grok 4.5 or Qwen3.6 27B
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.
Qwen3.6 27B: where it fits
A dense 27B multimodal model with its family's best coding score — it beats a 397B mixture-of-experts, but costs more per token. Released April 22, 2026 by Alibaba, it is built for the best open coding score in its family — 77.2% on SWE-Bench Verified, beating Alibaba's own 397B mixture-of-experts at a fifteenth of the size, dense, so quality per gigabyte of VRAM is high: it fits one consumer GPU when quantised, far stronger agentic work than its sparse sibling (59.3 against 51.5 on Terminal-Bench 2.0), and dense models fine-tune far more predictably than mixture-of-experts models do.
Its trade-offs: every parameter fires on every token, so it is slower and costlier per token than the sparse 35B, hosted output pricing is the harshest in its family, and provider input prices moved by roughly half in a single quarter, and its SWE-Bench score comes from Alibaba's internal scaffold rather than the standard public harness. 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. Qwen3.6 27B gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Grok 4.5 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 Grok 4.5 and Qwen3.6 27B 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 Grok 4.5, 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 Qwen3.6 27B leans toward the best open coding score in its family — 77.2% on swe-bench verified, beating alibaba's own 397b mixture-of-experts at a fifteenth of the size, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Grok 4.5 or Qwen3.6 27B?
Qwen3.6 27B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Grok 4.5 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?
Grok 4.5 — 500K vs 256K, about 1.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4.5 and Qwen3.6 27B together?
Yes — a multi-model platform like LumiChats gives you Grok 4.5, Qwen3.6 27B 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 Qwen3.6 27B?
Grok 4.5 — released July 8, 2026, about 3 months after Qwen3.6 27B.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.