Both target deployable open weights under Apache 2.0. Qwen3.5's family wins on breadth and per-size quality — its 9B variant with 256K context is the standout local model of the generation. gpt-oss counters with OpenAI provenance and the 120B's clever single-80GB-GPU fit. For most local and mid-scale deployments, Qwen3.5 is the stronger recommendation.
gpt-oss vs Qwen3.5 at a glance
| gpt-oss | Qwen3.5 | |
|---|---|---|
| Vendor | OpenAI (United States) | Alibaba (Qwen team) (China) |
| Open weights | Yes — downloadable | Yes — downloadable |
| License | Apache 2.0 — permissive, patent-granting, free for commercial use | Apache 2.0 — permissive, patent-granting, free for commercial use |
| Parameters | 117B (gpt-oss-120b) / 21B (gpt-oss-20b) (5.1B / 3.6B active) | 397B (17B active) |
| Context window | 128K tokens | 262K tokens (native) |
| Modalities | text | text |
| Pricing | Varies by hosting provider (open weights) | Varies by hosting provider (open weights) |
| Released | 2025-08-05 | 2026-02-16 |
Specs and pricing verified July 2026.
About gpt-oss
gpt-oss is OpenAI's return to open weights — its first since GPT-2. The August 2025 release shipped two MoE reasoning models under Apache 2.0: gpt-oss-120b (117B total, 5.1B active, single-80GB-GPU serving in native MXFP4) and gpt-oss-20b (21B total, runs on a 16GB consumer GPU), both with configurable reasoning effort and 128K context.
Strategically it validated the open-weight thesis from the least likely vendor, and practically the 20B became one of the most-run local models in the world — the default 'serious model on a laptop.' For pure capability the 2026 Chinese frontier models outclass it, but for accessible, US-origin, Apache-2.0 deployment it remains a staple.
Full specs, benchmarks, and hardware guidance: the gpt-oss page.
About Qwen3.5
Qwen3.5 is Alibaba's February 2026 generation and the efficiency benchmark of the open-weight field: the 397B-A17B flagship activates just 17B parameters per token yet beats Alibaba's own trillion-parameter Qwen3-Max — at 8.6× the throughput at 32K context and 19× at 256K. All open-weight variants ship under Apache 2.0, the most enterprise-friendly license in common use.
The release is a full family, not one model: from the 397B flagship down to a 9B variant with a native 256K context window that runs on consumer hardware. That spread — one architecture, Apache 2.0 everywhere, sizes from phone to datacenter — is why Qwen has become the default base-model family for fine-tuners and the most-adopted open-weight line by download count.
Full specs, benchmarks, and hardware guidance: the Qwen3.5 page.
Choosing between them
Choose gpt-oss for:
- Local deployment on consumer hardware (20B on a 16GB GPU)
- US-origin open weights under Apache 2.0 for policy-constrained buyers
- Configurable reasoning-effort workloads
Choose Qwen3.5 for:
- Enterprise deployments that require Apache 2.0 licensing
- Efficiency-critical serving (17B active parameters, extreme throughput)
- Fine-tuning projects — the broadest size ladder in open weights
Frequently asked questions
Is gpt-oss better than Qwen3.5?
Both target deployable open weights under Apache 2.0. Qwen3.5's family wins on breadth and per-size quality — its 9B variant with 256K context is the standout local model of the generation. gpt-oss counters with OpenAI provenance and the 120B's clever single-80GB-GPU fit. For most local and mid-scale deployments, Qwen3.5 is the stronger recommendation.
Which is cheaper: gpt-oss or Qwen3.5?
gpt-oss: Varies by hosting provider (open weights). Qwen3.5: Varies by hosting provider (open weights). Both are open-weight, so self-hosting costs depend on your hardware and utilization.
Can I self-host gpt-oss and Qwen3.5?
gpt-oss: yes — weights are published under Apache 2.0. Qwen3.5: yes — weights are published under Apache 2.0.