DeepSeek V4 Pro vs Qwen3.5-35B-A3B

DeepSeek V4 Pro (2026) and Qwen3.5-35B-A3B (2026) are frontier-tier reasoning models from DeepSeek and Alibaba. DeepSeek V4 Pro ships a 1M-token context window, while Qwen3.5-35B-A3B ships a 256K-token context window. On MMLU PRO, DeepSeek V4 Pro leads by 2.2 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

DeepSeek V4 Pro is safer overall; choose Qwen3.5-35B-A3B when provider fit matters.

Decision scorecard

Local evidence first
SignalDeepSeek V4 ProQwen3.5-35B-A3B
Best forreasoning-heavy apps, tool-calling agents, and long-context analysisreasoning-heavy apps, tool-calling agents, and provider-routed production
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window1M256K
Cheapest output$0.73/1M tokens$1.30/1M tokens
Provider routes6 tracked2 tracked
Shared benchmarksMMLU PRO leader5 shared

Decision tradeoffs

Choose DeepSeek V4 Pro when...
  • DeepSeek V4 Pro holds a shared-benchmark lead on MMLU PRO, ahead by 2.2 points.
  • DeepSeek V4 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • DeepSeek V4 Pro has the lower cheapest tracked output price at $0.73/1M tokens.
  • DeepSeek V4 Pro has broader tracked provider coverage for fallback and route flexibility.
  • Local decision data tags DeepSeek V4 Pro for Coding, RAG, and Agents.
Choose Qwen3.5-35B-A3B when...
  • Local decision data tags Qwen3.5-35B-A3B for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate Qwen3.5-35B-A3B

DeepSeek V4 Pro

$472

Cheapest tracked route/tier: OpenRouter

Qwen3.5-35B-A3B

$455

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $17.31. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

DeepSeek V4 Pro -> Qwen3.5-35B-A3B
  • Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
  • Qwen3.5-35B-A3B is $0.57/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Qwen3.5-35B-A3B -> DeepSeek V4 Pro
  • Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
  • DeepSeek V4 Pro is $0.57/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.

Specs

Specification
Released2026-04-242026-02-24
Context window1M256K
Parameters1.6T35B
ArchitectureMixture of ExpertsMixture of Experts
LicenseMITOSI-approvedApache 2.0OSI-approved
OpennessOpen sourceOpen source
WeightsAvailableAvailable
CodeUnknownUnknown
Commercial usePermittedPermitted
Knowledge cutoff--

Pricing and availability

Pricing attributeDeepSeek V4 ProQwen3.5-35B-A3B
Input price
Off-peak
$0.66/1M tokens
All hours outside DeepSeek peak windows, including weekends and Chinese public holidays. Cache-read input: $0.022 per 1M tokens; cache-miss input: $0.66 per 1M; output: $1.98 per 1M.
Peak
$1.32/1M tokens
01:00-04:00 and 06:00-10:00 UTC, Monday-Friday, excluding Chinese public holidays. 2x off-peak. Cache-read input: $0.044 per 1M tokens; cache-miss input: $1.32 per 1M; output: $3.96 per 1M.
$0.16/1M tokens
Output price
Off-peak
$1.98/1M tokens
All hours outside DeepSeek peak windows, including weekends and Chinese public holidays. Cache-read input: $0.022 per 1M tokens; cache-miss input: $0.66 per 1M; output: $1.98 per 1M.
Peak
$3.96/1M tokens
01:00-04:00 and 06:00-10:00 UTC, Monday-Friday, excluding Chinese public holidays. 2x off-peak. Cache-read input: $0.044 per 1M tokens; cache-miss input: $1.32 per 1M; output: $3.96 per 1M.
$1.30/1M tokens
Providers

Capabilities

CapabilityDeepSeek V4 ProQwen3.5-35B-A3B
VisionNoNo
MultimodalNoNo
ReasoningYesYes
JSON / Tool useYesYes
Structured outputsYesYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkDeepSeek V4 ProQwen3.5-35B-A3B
MMLU PRO87.585.3
SWE-bench Verified80.669.2
Google-Proof Q&A90.184.5
LiveCodeBench93.574.6
Humanity's Last Exam37.722.4

Deep dive

On shared benchmark coverage, MMLU PRO has DeepSeek V4 Pro at 87.5 and Qwen3.5-35B-A3B at 85.3, with DeepSeek V4 Pro ahead by 2.2 points; SWE-bench Verified has DeepSeek V4 Pro at 80.6 and Qwen3.5-35B-A3B at 69.2, with DeepSeek V4 Pro ahead by 11.4 points; Google-Proof Q&A has DeepSeek V4 Pro at 90.1 and Qwen3.5-35B-A3B at 84.5, with DeepSeek V4 Pro ahead by 5.6 points. The largest visible gap is 11.4 points on SWE-bench Verified, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint is close: both models cover reasoning mode, JSON / Tool use, and structured outputs. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

For cost, DeepSeek V4 Pro lists tiered pricing: Off-peak is $0.66/1M input and $1.98/1M output; Peak is $1.32/1M input and $3.96/1M output, while Qwen3.5-35B-A3B lists $0.16/1M input and $1.30/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V4 Pro lower by about $0.03 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 6 providers versus 2, so concentration risk also matters.

Choose DeepSeek V4 Pro when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose Qwen3.5-35B-A3B when provider fit and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.

FAQ

Which has a larger context window, DeepSeek V4 Pro or Qwen3.5-35B-A3B?

DeepSeek V4 Pro supports 1M tokens, while Qwen3.5-35B-A3B supports 256K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, DeepSeek V4 Pro or Qwen3.5-35B-A3B?

DeepSeek V4 Pro lists tiered pricing: Off-peak is $0.66/1M input and $1.98/1M output; Peak is $1.32/1M input and $3.96/1M output. Qwen3.5-35B-A3B lists $0.16/1M input and $1.30/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.

Is DeepSeek V4 Pro or Qwen3.5-35B-A3B open source?

DeepSeek V4 Pro is listed under MIT. Qwen3.5-35B-A3B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for reasoning mode, DeepSeek V4 Pro or Qwen3.5-35B-A3B?

Both DeepSeek V4 Pro and Qwen3.5-35B-A3B expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for JSON / Tool use, DeepSeek V4 Pro or Qwen3.5-35B-A3B?

Both DeepSeek V4 Pro and Qwen3.5-35B-A3B expose JSON / Tool use. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Where can I run DeepSeek V4 Pro and Qwen3.5-35B-A3B?

DeepSeek V4 Pro is available on DeepSeek Platform, Fireworks AI, OpenRouter, Vercel AI Gateway, and Novita AI. Qwen3.5-35B-A3B is available on OpenRouter and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-10-17. Data sourced from public model cards and provider documentation.