AI Models · Open-Source vs Paid

Qwen3.8 Max Open vs o1-pro (batch) Paid

Qwen3.8 Max vs o1-pro (batch) compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.

Prices & specs refreshed from live data · olud.ai

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

Qwen3.8 MaxOpenAlibaba
$2 /M input
$6 /M outputNo per-token fees if you self-host
TypeOpen-weight
Context window1M tokens
MultimodalYes
Self-hostYes
o1-pro (batch)PaidOpenAI
$75 /M input
$300 /M outputManaged API (no infra to run)
TypeProprietary
Context window200K tokens
MultimodalYes
Self-hostNo
Choose Qwen3.8 Max if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose o1-pro (batch) if you want frontier capability through a managed API with zero infrastructure to run.

Qwen3.8 Max vs o1-pro (batch) specs

SpecQwen3.8 Maxo1-pro (batch)Winner
MakerAlibabaOpenAI
TypeOpen-weightProprietaryQwen3.8 Max
Context window1M tokens200K tokensQwen3.8 Max
Input price$2/M · free self-host$75/MQwen3.8 Max
Output price$6/M · free self-host$300/MQwen3.8 Max
Vision / multimodalYesYes= Tie
Tool / function callingYesNoQwen3.8 Max
Self-hostableYesNo (API only)Qwen3.8 Max
LicenseApache 2.0ProprietaryQwen3.8 Max

Price gap & when to choose each

50×cheaper per output token

Qwen3.8 Max is ~50× cheaper than o1-pro (batch) on output tokens ($6 vs $300 per M tokens).

Choose Qwen3.8 Max if…
  • You want to self-host or run on your cloud
  • You need the longer 1M context window
  • You prioritize data privacy & control
  • You want the lowest operating costs
  • You are building open or reproducible AI
Choose o1-pro (batch) if…
  • You want frontier performance through a managed API
  • You value reliability & ecosystem
  • You don't want to manage infrastructure

Feature comparison

CapabilityQwen3.8 Maxo1-pro (batch)
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: Qwen3.8 Max vs o1-pro (batch)

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

Qwen3.8 Max delivers 194× more intelligence per dollar.
Qwen3.8 Max
o1-pro (batch)
Intelligence index
58.1
19.1
Coding index
71.8
GPQA
92.7%
Humanity's Last Exam
43%
Long Context Reasoning
74.3%
SciCode
52.9%
τ-Bench Banking
51.3%
Terminal-Bench
81.3%
Speed
47.1 tok/s
0 tok/s
Latency
1.82s
0s
Intelligence per $
19.4
0.1

Benchmark data by Artificial Analysis.

How Qwen3.8 Max and o1-pro (batch) score

🏆 Best value & openness: Qwen3.8 Max (4.8 vs 2.4 / 5)
CriterionQwen3.8 Maxo1-pro (batch)
Cost-efficiency4.02.0
Context window5.04.0
Openness5.01.5
Self-hosting5.01.0
Multimodality5.03.5

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

Qwen3.8 Max Open

Alibaba · Open-weight

Qwen3.8 Max is the flagship model in Alibaba's Qwen3.8 series, the general-availability successor to the Qwen3.8 Max Preview. It is a multimodal reasoning model intended for complex reasoning, visual understanding,...

o1-pro (batch) Paid

OpenAI · Proprietary

The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide...

Other models in these families

These variants are tracked but not compared here — one page per family keeps the comparison readable.

Other variants tracked
Qwen3.8 2.4T A95BQwen3.8 27BQwen3.7 MaxQwen3.6 Max PreviewQwen3.6 PlusQwen3.7 PlusQwen3.6 27BQwen3.5-27BQwen3.5 397B A17BQwen3.5-122B-A10BQwen3 Max ThinkingQwen3.6 35B A3BQwen3.5-35B-A3BQwen3 MaxQwen3.5-9BQwen3 Coder NextQwen3 VL 235B A22B ThinkingQwen3 235B A22B Thinking 2507Qwen3 235B A22B Instruct 2507Qwen3 Coder 480B A35BQwen3 Next 80B A3B ThinkingQwen3 30B A3B Thinking 2507Qwen3 VL 235B A22B InstructQwen3 Next 80B A3B InstructQwen3 Coder 30B A3B InstructQwen3 235B A22BQwen3 VL 30B A3B ThinkingQwen3 32BQwen3 VL 32B InstructQwen3 VL 8B ThinkingQwen3 14BQwen3 VL 30B A3B InstructQwen2.5 72B InstructQwen3 30B A3BQwen3 30B A3B Instruct 2507Qwen3 8BQwen3 VL 8B InstructQwen2.5 Coder 32B InstructQwen3 Coder PlusQwen3.5 Plus 2026-04-20Qwen3.5 Plus 2026-02-15Qwen3.6 FlashQwen2.5 VL 72B InstructQwen3 Coder FlashQwen-PlusQwen Plus 0728Qwen Plus 0728 (thinking)Qwen3.5-FlashQwen2.5 7B InstructQwen3.7 Flash

Frequently asked questions

Is Qwen3.8 Max as good as o1-pro (batch)?

Qwen3.8 Max is open-weight and competitive on many tasks, but o1-pro (batch) may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.

Can I run Qwen3.8 Max locally?

Yes. Qwen3.8 Max has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. o1-pro (batch) is API-only and cannot be self-hosted.

How much cheaper is Qwen3.8 Max?

Qwen3.8 Max costs $6/M output vs $300/M for o1-pro (batch) — roughly 50x cheaper via API, and free if you self-host.

Qwen3.8 Max vs o1-pro (batch) — which should I pick in 2026?

Choose Qwen3.8 Max if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose o1-pro (batch) if you want frontier capability through a managed API with zero infrastructure to run.

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