Pick Claude Opus 4.7 for long-running agentic coding workflows or precise instruction following. Pick Qwen3.6 35B A3B for extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost or runs at roughly 120 tokens per second on a single 24gb consumer gpu. Choose Qwen3.6 35B A3B if you need self-hosting or data privacy; Claude Opus 4.7 if you want a managed API.
Claude Opus 4.7 (Anthropic, US) and Qwen3.6 35B A3B (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. Claude Opus 4.7 is the agentic-coding-focused Opus that traded some long-context recall for long-run reliability. Qwen3.6 35B A3B is a sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. They diverge most on price, context window, open vs. closed weights and coding benchmarks — each quantified below from the models' real specs.
Key differences
Cost model: Qwen3.6 35B A3B ships open weights you can self-host (hardware cost only, no per-token fee), while Claude Opus 4.7 is API-metered at $5/$25 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: Claude Opus 4.7 holds 3.8× more — 1M (~1,500 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.
Coding: Claude Opus 4.7 leads SWE-Bench Verified by 14.2 points (87.6% vs 73.4%) — a real edge on hard, real-world software tasks.
Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Claude Opus 4.7
Qwen3.6 35B A3B
Provider
Anthropic (US)
Alibaba (China)
Released
April 16, 2026
April 16, 2026
Context window
1M (~1,500 pages)
256K (~393 pages)
Price (in/out)
$5/$25 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
87.6%
73.4%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-running agentic coding workflows: Claude Opus 4.7 — It scores 87.6% on SWE-Bench Verified against Qwen3.6 35B A3B's 73.4% — a 14.2-point edge on real repository work.
Precise instruction following: Claude Opus 4.7 — The agentic-coding-focused Opus that traded some long-context recall for long-run reliability — and it leads SWE-Bench Verified 87.6% to 73.4%.
Task budgets and effort tiers: Claude Opus 4.7 — The agentic-coding-focused Opus that traded some long-context recall for long-run reliability — and it carries the larger 1M context.
Extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost: Qwen3.6 35B A3B — A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware — and its weights are open while Claude Opus 4.7 is API-only.
Runs at roughly 120 tokens per second on a single 24GB consumer GPU: Qwen3.6 35B A3B — Qwen3.6 35B A3B lists runs at roughly 120 tokens per second on a single 24GB consumer GPU among its strengths; Claude Opus 4.7 does not.
Apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN: Qwen3.6 35B A3B — Claude Opus 4.7 is comparatively weak here — long-context recall regressed vs 4.6
Lowest cost at scale: Qwen3.6 35B A3B — Its weights are open, so at volume you pay for your own hardware instead of Claude Opus 4.7's $5/$25 per 1M tokens.
Largest single-prompt input: Claude Opus 4.7 — Its 1M window is about 3.8× larger than Qwen3.6 35B A3B's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Qwen3.6 35B A3B — At Open weight (self-host / free) it undercuts Claude Opus 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Claude Opus 4.7 — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: Qwen3.6 35B A3B — Open weights let you run it on your own hardware; Claude Opus 4.7 is API-only.
Anyone whose priority is long-running agentic coding workflows: Claude Opus 4.7 — It is specifically built for that.
Anyone whose priority is extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost: Qwen3.6 35B A3B — That is its strongest area.
An enterprise with regional data-residency rules: Claude Opus 4.7 or Qwen3.6 35B A3B — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Claude Opus 4.7: where it fits
The agentic-coding-focused Opus that traded some long-context recall for long-run reliability. Released April 16, 2026 by Anthropic, it is built for long-running agentic coding workflows, precise instruction following, task budgets and effort tiers, and large-codebase operation.
Its trade-offs are real: long-context recall regressed vs 4.6, and superseded by Opus 4.8. At $5 in / $25 out per million tokens, it sits in the premium price band.
Qwen3.6 35B A3B: where it fits
A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. Released April 16, 2026 by Alibaba, it is built for extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost, runs at roughly 120 tokens per second on a single 24GB consumer GPU, apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN, and preserves its reasoning across turns, which cuts the overhead of agentic loops.
Its trade-offs: loses to its smaller dense sibling Qwen3.6 27B on every coding benchmark, despite more total parameters, its SWE-Bench score comes from Alibaba's internal scaffold rather than the standard public harness, and all 35B parameters must stay resident in VRAM even though only 3B compute per token. 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 35B A3B gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Claude Opus 4.7 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 Claude Opus 4.7 or Qwen3.6 35B A3B better for coding?
On SWE-Bench Verified, Claude Opus 4.7 scores 87.6% and Qwen3.6 35B A3B scores 73.4% — Claude Opus 4.7 has the measurable edge.
Which is cheaper, Claude Opus 4.7 or Qwen3.6 35B A3B?
Qwen3.6 35B A3B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Opus 4.7 is API-metered at $5/$25 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?
Claude Opus 4.7 — 1M vs 256K, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Opus 4.7 and Qwen3.6 35B A3B together?
Yes — a multi-model platform like LumiChats gives you Claude Opus 4.7, Qwen3.6 35B A3B 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, Claude Opus 4.7 or Qwen3.6 35B A3B?
They were released around the same time (April 16, 2026 and April 16, 2026).
Claude Opus 4.7 vs Qwen3.6 35B A3B
Anthropic · US | Alibaba · China · Updated June 2026
Quick verdict
Pick Claude Opus 4.7 for long-running agentic coding workflows or precise instruction following. Pick Qwen3.6 35B A3B for extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost or runs at roughly 120 tokens per second on a single 24gb consumer gpu. Choose Qwen3.6 35B A3B if you need self-hosting or data privacy; Claude Opus 4.7 if you want a managed API.
Claude Opus 4.7 (Anthropic, US) and Qwen3.6 35B A3B (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. Claude Opus 4.7 is the agentic-coding-focused Opus that traded some long-context recall for long-run reliability. Qwen3.6 35B A3B is a sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. They diverge most on price, context window, open vs. closed weights and coding benchmarks — each quantified below from the models' real specs.
Key differences at a glance
▸Cost model: Qwen3.6 35B A3B ships open weights you can self-host (hardware cost only, no per-token fee), while Claude Opus 4.7 is API-metered at $5/$25 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: Claude Opus 4.7 holds 3.8× more — 1M (~1,500 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.
▸Coding: Claude Opus 4.7 leads SWE-Bench Verified by 14.2 points (87.6% vs 73.4%) — a real edge on hard, real-world software tasks.
▸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
Claude Opus 4.7
Qwen3.6 35B A3B
Provider
Anthropic (US)
Alibaba (China)
Released
April 16, 2026
April 16, 2026
Context window
1M (~1,500 pages)
256K (~393 pages)
Price (in/out)
$5/$25 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
87.6%
73.4%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-running agentic coding workflows
Claude Opus 4.7
It scores 87.6% on SWE-Bench Verified against Qwen3.6 35B A3B's 73.4% — a 14.2-point edge on real repository work.
Precise instruction following
Claude Opus 4.7
The agentic-coding-focused Opus that traded some long-context recall for long-run reliability — and it leads SWE-Bench Verified 87.6% to 73.4%.
Task budgets and effort tiers
Claude Opus 4.7
The agentic-coding-focused Opus that traded some long-context recall for long-run reliability — and it carries the larger 1M context.
Extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost
Qwen3.6 35B A3B
A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware — and its weights are open while Claude Opus 4.7 is API-only.
Runs at roughly 120 tokens per second on a single 24GB consumer GPU
Qwen3.6 35B A3B
Qwen3.6 35B A3B lists runs at roughly 120 tokens per second on a single 24GB consumer GPU among its strengths; Claude Opus 4.7 does not.
Apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN
Qwen3.6 35B A3B
Claude Opus 4.7 is comparatively weak here — long-context recall regressed vs 4.6
Lowest cost at scale
Qwen3.6 35B A3B
Its weights are open, so at volume you pay for your own hardware instead of Claude Opus 4.7's $5/$25 per 1M tokens.
Largest single-prompt input
Claude Opus 4.7
Its 1M window is about 3.8× larger than Qwen3.6 35B A3B's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen3.6 35B A3B
At Open weight (self-host / free) it undercuts Claude Opus 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Claude Opus 4.7
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Qwen3.6 35B A3B
Open weights let you run it on your own hardware; Claude Opus 4.7 is API-only.
Anyone whose priority is long-running agentic coding workflows
→ Claude Opus 4.7
It is specifically built for that.
Anyone whose priority is extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost
→ Qwen3.6 35B A3B
That is its strongest area.
An enterprise with regional data-residency rules
→ Claude Opus 4.7 or Qwen3.6 35B A3B
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Claude Opus 4.7: where it fits
The agentic-coding-focused Opus that traded some long-context recall for long-run reliability. Released April 16, 2026 by Anthropic, it is built for long-running agentic coding workflows, precise instruction following, task budgets and effort tiers, and large-codebase operation.
Its trade-offs are real: long-context recall regressed vs 4.6, and superseded by Opus 4.8. At $5 in / $25 out per million tokens, it sits in the premium price band.
Qwen3.6 35B A3B: where it fits
A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. Released April 16, 2026 by Alibaba, it is built for extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost, runs at roughly 120 tokens per second on a single 24GB consumer GPU, apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN, and preserves its reasoning across turns, which cuts the overhead of agentic loops.
Its trade-offs: loses to its smaller dense sibling Qwen3.6 27B on every coding benchmark, despite more total parameters, its SWE-Bench score comes from Alibaba's internal scaffold rather than the standard public harness, and all 35B parameters must stay resident in VRAM even though only 3B compute per token. 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 35B A3B gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Claude Opus 4.7 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 Claude Opus 4.7 and Qwen3.6 35B A3B 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 Claude Opus 4.7 or Qwen3.6 35B A3B better for coding?
On SWE-Bench Verified, Claude Opus 4.7 scores 87.6% and Qwen3.6 35B A3B scores 73.4% — Claude Opus 4.7 has the measurable edge.
Which is cheaper, Claude Opus 4.7 or Qwen3.6 35B A3B?
Qwen3.6 35B A3B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Opus 4.7 is API-metered at $5/$25 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?
Claude Opus 4.7 — 1M vs 256K, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Opus 4.7 and Qwen3.6 35B A3B together?
Yes — a multi-model platform like LumiChats gives you Claude Opus 4.7, Qwen3.6 35B A3B 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, Claude Opus 4.7 or Qwen3.6 35B A3B?
They were released around the same time (April 16, 2026 and April 16, 2026).
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.