AI Models · Open-Source Alternatives

Open-Source Alternatives to GPT-3.5 Turbo (batch)

The best open-weight, self-hostable alternatives to GPT-3.5 Turbo (batch) in 2026 — compared on price, context window and capabilities. Run them locally and cut API costs.

Refreshed from live data · olud.ai

The best open-weight alternatives to GPT-3.5 Turbo (batch)

GPT-3.5 Turbo (batch) is a proprietary, API-only model. These open-weight models can be self-hosted, run offline and used at a fraction of the cost — here's how the top ones stack up.

DeepSeek V4.1 Flash Open

DeepSeek · 1M ctx · $0.6/M out

34.0 pts ABOVE GPT-3.5 Turbo (batch) on the Artificial Analysis intelligence index · 1.3× cheaper per million output tokens

DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture. It activates 8B parameters on input and 16B on...

DeepSeek V4.1 Flash vs GPT-3.5 Turbo (batch) →

Hy3 Open

Tencent · 262K ctx · $0.33/M out

20.3 pts ABOVE GPT-3.5 Turbo (batch) on the Artificial Analysis intelligence index · 2.3× cheaper per million output tokens

Hy3 is a 295B-parameter Mixture-of-Experts model from Tencent (21B active, 192 experts with top-8 routing) built for reasoning, agentic workflows, and real-world production use. It supports a configurable reasoning effort:...

Hy3 vs GPT-3.5 Turbo (batch) →

IN Ling 3.0 Flash Open

Inclusionai · 262K ctx · $0.06/M out

19.4 pts ABOVE GPT-3.5 Turbo (batch) on the Artificial Analysis intelligence index · 12.5× cheaper per million output tokens

*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*. The model is designed with *token efficiency and production-scale agentic inference* as key priorities, enablin

Ling 3.0 Flash vs GPT-3.5 Turbo (batch) →

Gemma 4 26B A4B Open

Google · 262K ctx · $0.22/M out

11.2 pts ABOVE GPT-3.5 Turbo (batch) on the Artificial Analysis intelligence index · 3.4× cheaper per million output tokens

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...

Gemma 4 26B A4B vs GPT-3.5 Turbo (batch) →

North Mini Code (free) Open

Cohere · 256K ctx · Free/M out

7.3 pts ABOVE GPT-3.5 Turbo (batch) on the Artificial Analysis intelligence index

North Mini Code is Cohere's first agentic coding model and the debut of its North family. A sparse mixture-of-experts model with 30B total parameters and 3B active, it is optimized...

North Mini Code (free) vs GPT-3.5 Turbo (batch) →

gpt-oss-120b (batch) Open

OpenAI · 131K ctx · $0.6/M out

6.8 pts ABOVE GPT-3.5 Turbo (batch) on the Artificial Analysis intelligence index · 1.3× cheaper per million output tokens

gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimize

gpt-oss-120b (batch) vs GPT-3.5 Turbo (batch) →

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