Pick DeepSeek V4 for near-frontier coding at ~1/12 the cost or open mit-licensed weights you can self-host. Pick Qwen3 235B A22B for deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux) or exceptional multilingual and alignment results (79.2 arena-hard v2, 85.2 writingbench). On a tight budget at scale, Qwen3 235B A22B is the value pick.
DeepSeek V4 (DeepSeek) and Qwen3 235B A22B (Alibaba) are two of the models people most often weigh against each other in 2026. DeepSeek V4 is china's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. Qwen3 235B A22B is an older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: DeepSeek V4 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.
Recency: DeepSeek V4 is the newer model by about 9 months (released April 24, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
DeepSeek V4
Qwen3 235B A22B
Provider
DeepSeek (China)
Alibaba (China)
Released
April 24, 2026
July 21, 2025
Context window
1M (~1,500 pages)
256K (~393 pages)
Price (in/out)
$0.435/$0.87 per 1M tokens
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
80.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Near-frontier coding at ~1/12 the cost: DeepSeek V4 — Qwen3 235B A22B is comparatively weak here — coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on
Open MIT-licensed weights you can self-host: DeepSeek V4 — Qwen3 235B A22B is comparatively weak here — its 235B weights need roughly 438GB in BF16, far beyond consumer hardware
No long-context surcharge: DeepSeek V4 — Its 1M window holds about 3.8× more than Qwen3 235B A22B's 256K in a single prompt.
Deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux): Qwen3 235B A22B — Qwen3 235B A22B lists deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux) among its strengths; DeepSeek V4 does not.
Exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench): Qwen3 235B A22B — Qwen3 235B A22B lists exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench) among its strengths; DeepSeek V4 does not.
Outstanding structured logic — 95.0 on ZebraLogic: Qwen3 235B A22B — Qwen3 235B A22B lists outstanding structured logic — 95.0 on ZebraLogic among its strengths; DeepSeek V4 does not.
Lowest cost at scale: Qwen3 235B A22B — Its weights are open, so at volume you pay for your own hardware instead of DeepSeek V4's $0.435/$0.87 per 1M tokens.
Largest single-prompt input: DeepSeek V4 — Its 1M window is about 3.8× larger than Qwen3 235B A22B's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Qwen3 235B A22B — At Open weight (self-host / free) it undercuts DeepSeek V4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: DeepSeek V4 — Larger 1M window fits more in one prompt.
Anyone whose priority is near-frontier coding at ~1/12 the cost: DeepSeek V4 — It is specifically built for that.
Anyone whose priority is deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux): Qwen3 235B A22B — That is its strongest area.
DeepSeek V4: where it fits
China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. Released April 24, 2026 by DeepSeek, it is built for near-frontier coding at ~1/12 the cost, open MIT-licensed weights you can self-host, no long-context surcharge, and highest LiveCodeBench result.
Its trade-offs are real: trails the very best on hardest agentic coding, and text/code focused, less multimodal. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
Qwen3 235B A22B: where it fits
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. Released July 21, 2025 by Alibaba, it is built for deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux), exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench), outstanding structured logic — 95.0 on ZebraLogic, and no thinking mode, which makes latency and token spend entirely predictable.
Its trade-offs: nearly a year old and superseded — Artificial Analysis now steers users to Qwen3.5-397B instead, text-only with no vision, and the absence of a thinking mode caps its hardest reasoning, coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on, and its 235B weights need roughly 438GB in BF16, far beyond consumer hardware. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
DeepSeek V4 and Qwen3 235B A22B overlap enough that the right pick depends on your specific job. Qwen3 235B A22B costs less per token; DeepSeek V4 holds the larger context; and each leads in its own area — DeepSeek V4 for near-frontier coding at ~1/12 the cost, Qwen3 235B A22B for deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is DeepSeek V4 or Qwen3 235B A22B better for coding?
Public SWE-Bench figures are not available for Qwen3 235B A22B, so the honest test is your own repository — run an identical real bug through both. By design, DeepSeek V4 leans toward near-frontier coding at ~1/12 the cost while Qwen3 235B A22B leans toward deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4 or Qwen3 235B A22B?
Qwen3 235B A22B is cheaper — $0.435/$0.87 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
DeepSeek V4 — 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 DeepSeek V4 and Qwen3 235B A22B together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4, Qwen3 235B A22B 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, DeepSeek V4 or Qwen3 235B A22B?
DeepSeek V4 — released April 24, 2026, about 9 months after Qwen3 235B A22B.
DeepSeek V4 vs Qwen3 235B A22B
DeepSeek · China | Alibaba · China · Updated June 2026
Quick verdict
Pick DeepSeek V4 for near-frontier coding at ~1/12 the cost or open mit-licensed weights you can self-host. Pick Qwen3 235B A22B for deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux) or exceptional multilingual and alignment results (79.2 arena-hard v2, 85.2 writingbench). On a tight budget at scale, Qwen3 235B A22B is the value pick.
DeepSeek V4 (DeepSeek) and Qwen3 235B A22B (Alibaba) are two of the models people most often weigh against each other in 2026. DeepSeek V4 is china's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. Qwen3 235B A22B is an older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: DeepSeek V4 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.
▸Recency: DeepSeek V4 is the newer model by about 9 months (released April 24, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
DeepSeek V4
Qwen3 235B A22B
Provider
DeepSeek (China)
Alibaba (China)
Released
April 24, 2026
July 21, 2025
Context window
1M (~1,500 pages)
256K (~393 pages)
Price (in/out)
$0.435/$0.87 per 1M tokens
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
80.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Near-frontier coding at ~1/12 the cost
DeepSeek V4
Qwen3 235B A22B is comparatively weak here — coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on
Open MIT-licensed weights you can self-host
DeepSeek V4
Qwen3 235B A22B is comparatively weak here — its 235B weights need roughly 438GB in BF16, far beyond consumer hardware
No long-context surcharge
DeepSeek V4
Its 1M window holds about 3.8× more than Qwen3 235B A22B's 256K in a single prompt.
Deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux)
Qwen3 235B A22B
Qwen3 235B A22B lists deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux) among its strengths; DeepSeek V4 does not.
Exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench)
Qwen3 235B A22B
Qwen3 235B A22B lists exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench) among its strengths; DeepSeek V4 does not.
Outstanding structured logic — 95.0 on ZebraLogic
Qwen3 235B A22B
Qwen3 235B A22B lists outstanding structured logic — 95.0 on ZebraLogic among its strengths; DeepSeek V4 does not.
Lowest cost at scale
Qwen3 235B A22B
Its weights are open, so at volume you pay for your own hardware instead of DeepSeek V4's $0.435/$0.87 per 1M tokens.
Largest single-prompt input
DeepSeek V4
Its 1M window is about 3.8× larger than Qwen3 235B A22B's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen3 235B A22B
At Open weight (self-host / free) it undercuts DeepSeek V4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ DeepSeek V4
Larger 1M window fits more in one prompt.
Anyone whose priority is near-frontier coding at ~1/12 the cost
→ DeepSeek V4
It is specifically built for that.
Anyone whose priority is deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux)
→ Qwen3 235B A22B
That is its strongest area.
DeepSeek V4: where it fits
China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. Released April 24, 2026 by DeepSeek, it is built for near-frontier coding at ~1/12 the cost, open MIT-licensed weights you can self-host, no long-context surcharge, and highest LiveCodeBench result.
Its trade-offs are real: trails the very best on hardest agentic coding, and text/code focused, less multimodal. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
Qwen3 235B A22B: where it fits
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. Released July 21, 2025 by Alibaba, it is built for deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux), exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench), outstanding structured logic — 95.0 on ZebraLogic, and no thinking mode, which makes latency and token spend entirely predictable.
Its trade-offs: nearly a year old and superseded — Artificial Analysis now steers users to Qwen3.5-397B instead, text-only with no vision, and the absence of a thinking mode caps its hardest reasoning, coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on, and its 235B weights need roughly 438GB in BF16, far beyond consumer hardware. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
DeepSeek V4 and Qwen3 235B A22B overlap enough that the right pick depends on your specific job. Qwen3 235B A22B costs less per token; DeepSeek V4 holds the larger context; and each leads in its own area — DeepSeek V4 for near-frontier coding at ~1/12 the cost, Qwen3 235B A22B for deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both DeepSeek V4 and Qwen3 235B A22B 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 DeepSeek V4 or Qwen3 235B A22B better for coding?
Public SWE-Bench figures are not available for Qwen3 235B A22B, so the honest test is your own repository — run an identical real bug through both. By design, DeepSeek V4 leans toward near-frontier coding at ~1/12 the cost while Qwen3 235B A22B leans toward deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4 or Qwen3 235B A22B?
Qwen3 235B A22B is cheaper — $0.435/$0.87 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
DeepSeek V4 — 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 DeepSeek V4 and Qwen3 235B A22B together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4, Qwen3 235B A22B 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, DeepSeek V4 or Qwen3 235B A22B?
DeepSeek V4 — released April 24, 2026, about 9 months after Qwen3 235B A22B.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.