DeepSeek V4 vs Qwen 3.7 Plus

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 Qwen 3.7 Plus for reading screens and interacting with guis or generating code from visual references. Choose DeepSeek V4 if you need self-hosting or data privacy; Qwen 3.7 Plus if you want a managed API.

DeepSeek V4 (DeepSeek) and Qwen 3.7 Plus (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. Qwen 3.7 Plus is alibaba's cost-effective multimodal agent in the Qwen3.7 series, built to perceive scenes, read screens and GUIs, generate code from visual references, and navigate mobile apps end-to-end. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecDeepSeek V4Qwen 3.7 Plus
ProviderDeepSeek (China) Alibaba (China)
ReleasedApril 24, 2026 June 1, 2026
Context window1M (~1,500 pages) 1M (~1,500 pages)
Price (in/out)$0.435/$0.87 per 1M tokens $0.4/$1.6 per 1M tokens
Open weight?Yes — self-hostable No — API only
Modalitiestext, code text, image, video, code
SWE-Bench Verified80.6% Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Near-frontier coding at ~1/12 the cost

DeepSeek V4

A core design strength of DeepSeek V4.

Open MIT-licensed weights you can self-host

DeepSeek V4

A core design strength of DeepSeek V4.

No long-context surcharge

DeepSeek V4

A core design strength of DeepSeek V4.

Reading screens and interacting with GUIs

Qwen 3.7 Plus

A core design strength of Qwen 3.7 Plus.

Generating code from visual references

Qwen 3.7 Plus

A core design strength of Qwen 3.7 Plus.

Agentic tool use, verification, and autonomous iteration

Qwen 3.7 Plus

A core design strength of Qwen 3.7 Plus.

Lowest cost at scale

Qwen 3.7 Plus

At $0.4/$1.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Which should you pick?

A cost-sensitive startup shipping high volume

Qwen 3.7 Plus

At $0.4/$1.6 per 1M tokens it undercuts DeepSeek V4, and on millions of tokens that margin decides the monthly bill.

A team with data-privacy or self-hosting needs

DeepSeek V4

Open weights let you run it on your own hardware; Qwen 3.7 Plus is API-only.

Anyone whose priority is near-frontier coding at ~1/12 the cost

DeepSeek V4

It is specifically built for that.

Anyone whose priority is reading screens and interacting with guis

Qwen 3.7 Plus

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.

Qwen 3.7 Plus: where it fits

Alibaba's cost-effective multimodal agent in the Qwen3.7 series, built to perceive scenes, read screens and GUIs, generate code from visual references, and navigate mobile apps end-to-end. Released June 1, 2026 by Alibaba, it is built for reading screens and interacting with GUIs, generating code from visual references, agentic tool use, verification, and autonomous iteration, and cost-effective vision-language processing at 1M context.

Its trade-offs: proprietary and API-only, with no downloadable weights, and outputs text only, no image, audio, or video generation. At $0.4 in / $1.6 out per million tokens, it sits in the budget price band.

The bottom line for this matchup

The defining split here is open vs. closed. DeepSeek V4 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Qwen 3.7 Plus 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 DeepSeek V4 and Qwen 3.7 Plus 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 DeepSeek V4 or Qwen 3.7 Plus better for coding?

Public SWE-Bench figures are not available for Qwen 3.7 Plus, 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 Qwen 3.7 Plus leans toward reading screens and interacting with guis, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, DeepSeek V4 or Qwen 3.7 Plus?

DeepSeek V4 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Qwen 3.7 Plus is API-metered at $0.4/$1.6 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?

Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both DeepSeek V4 and Qwen 3.7 Plus together?

Yes — a multi-model platform like LumiChats gives you DeepSeek V4, Qwen 3.7 Plus 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 Qwen 3.7 Plus?

Qwen 3.7 Plus — released June 1, 2026, about 38 days after DeepSeek V4.

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.