AI Models · Open-Source vs Paid

Qwen3.8 Max (0902) Open vs GPT-6 Astra (batch) Paid

Qwen3.8 Max (0902) vs GPT-6 Astra (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.

GPT-6 Astra (batch) — full profile ›

Prices & specs refreshed from live data · olud.ai

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

Qwen3.8 Max (0902)OpenAlibaba
$2 /M input
$6 /M outputNo per-token fees if you self-host
TypeOpen-weight
Context window1M tokens
MultimodalYes
Self-hostYes
GPT-6 Astra (batch)PaidOpenAI
$5 /M input
$25 /M outputManaged API (no infra to run)
TypeProprietary
Context window1.1M tokens
MultimodalYes
Self-hostNo
Choose Qwen3.8 Max (0902) 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 GPT-6 Astra (batch) if you want frontier capability through a managed API with zero infrastructure to run.

Qwen3.8 Max (0902) vs GPT-6 Astra (batch) specs

SpecQwen3.8 Max (0902)GPT-6 Astra (batch)Winner
MakerAlibabaOpenAI–
TypeOpen-weightProprietaryQwen3.8 Max (0902)
Context window1M tokens1.1M tokensGPT-6 Astra (batch)
Input price$2/M · free self-host$5/MQwen3.8 Max (0902)
Output price$6/M · free self-host$25/MQwen3.8 Max (0902)
Vision / multimodalYesYes= Tie
Tool / function callingYesYes= Tie
Self-hostableYesNo (API only)Qwen3.8 Max (0902)
LicenseApache 2.0ProprietaryQwen3.8 Max (0902)

Price gap & when to choose each

4.2×cheaper per output token

Qwen3.8 Max (0902) is ~4.2× cheaper than GPT-6 Astra (batch) on output tokens ($6 vs $25 per M tokens).

Choose Qwen3.8 Max (0902) if…
  • You want to self-host or run on your cloud
  • You prioritize data privacy & control
  • You want the lowest operating costs
  • You are building open or reproducible AI
Choose GPT-6 Astra (batch) if…
  • You want frontier performance through a managed API
  • You need the longer 1.1M context window
  • You value reliability & ecosystem
  • You don't want to manage infrastructure

Feature comparison

CapabilityQwen3.8 Max (0902)GPT-6 Astra (batch)
Open weights (downloadable)✓✗
Self-hostable✓✗
Runs fully offline✓✗
Vision / multimodal✓✓
Tool / function calling✓✓
1M+ context window✓✓

Benchmarks: Qwen3.8 Max (0902) vs GPT-6 Astra (batch)

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

Qwen3.8 Max (0902) delivers 5.2× more intelligence per dollar.
Qwen3.8 Max (0902)
GPT-6 Astra (batch)
Intelligence index
40.3
52.8
Coding index
71.8
76.9
GPQA
92.7%
96.1%
Humanity's Last Exam
43%
54.7%
Long Context Reasoning
78.3%
80.7%
SciCode
53.2%
56.5%
τ-Bench Banking
51.3%
41.4%
Terminal-Bench
81.3%
88.4%
Speed
41.4 tok/s
64.2 tok/s
Latency
1.8s
215.68s
Intelligence per $
13.4
2.6

Benchmark data by Artificial Analysis.

How Qwen3.8 Max (0902) and GPT-6 Astra (batch) score

🏆 Best value & openness: Qwen3.8 Max (0902) (4.8 vs 3.1 / 5)
CriterionQwen3.8 Max (0902)GPT-6 Astra (batch)
Cost-efficiency4.03.0
Context window5.05.0
Openness5.01.5
Self-hosting5.01.0
Multimodality5.05.0

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 (0902) Open

Alibaba · Open-weight

Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text,...

GPT-6 Astra (batch) Paid

OpenAI · Proprietary

GPT-6 Astra is OpenAI's flagship model for demanding end-to-end work. It is suited for advanced analysis, software engineering, deep research, scientific work, and document creation, with particular strengths in long-horizon...

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 2.4T A95B (batch)Qwen3.8 27BQwen3.7 MaxQwen3.6 Max PreviewQwen3.6 PlusQwen3.7 PlusQwen3.5-27BQwen3.6 27BQwen3.5 397B A17BQwen3 Max ThinkingQwen3.5-35B-A3BQwen3.6 35B A3BQwen3.5-122B-A10BQwen3 MaxQwen3.5-9B (batch)Qwen3.5-9BQwen3 VL 235B A22B ThinkingQwen3 235B A22B Thinking 2507Qwen3 235B A22B Instruct 2507Qwen3 Coder 480B A35BQwen3 Next 80B A3B ThinkingQwen3 Coder NextQwen3 VL 235B A22B InstructQwen3 30B A3B Thinking 2507Qwen3 Next 80B A3B InstructQwen3 Coder 30B A3B InstructQwen3 VL 30B A3B ThinkingQwen3 235B A22BQwen3 VL 32B InstructQwen3 VL 8B ThinkingQwen3 VL 30B A3B InstructQwen2.5 72B InstructQwen3 30B A3BQwen3 30B A3B Instruct 2507Qwen3 VL 8B InstructQwen3 32BQwen2.5 Coder 32B InstructQwen3 14BQwen3 8BQwen3 Coder PlusQwen3.5 Plus 2026-04-20Qwen3.5 Plus 2026-02-15Qwen3.6 FlashQwen2.5 VL 72B InstructQwen3 Coder FlashQwen-PlusQwen Plus 0728Qwen3.8 FlashQwen3.5-FlashQwen2.5 7B InstructQwen3.7 Flash

Frequently asked questions

Is Qwen3.8 Max (0902) as good as GPT-6 Astra (batch)?

Qwen3.8 Max (0902) is open-weight and competitive on many tasks, but GPT-6 Astra (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 (0902) locally?

Yes. Qwen3.8 Max (0902) has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. GPT-6 Astra (batch) is API-only and cannot be self-hosted.

How much cheaper is Qwen3.8 Max (0902)?

Qwen3.8 Max (0902) costs $6/M output vs $25/M for GPT-6 Astra (batch) — roughly 4x cheaper via API, and free if you self-host.

Qwen3.8 Max (0902) vs GPT-6 Astra (batch) — which should I pick in 2026?

Choose Qwen3.8 Max (0902) 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 GPT-6 Astra (batch) if you want frontier capability through a managed API with zero infrastructure to run.

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