Ling 3.0 Flash vs GPT-3.5 Turbo 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-3.5 Turbo — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
| Spec | Ling 3.0 Flash | GPT-3.5 Turbo | Winner |
|---|---|---|---|
| Maker | Inclusionai | OpenAI | – |
| Type | Open-weight | Proprietary | INLing 3.0 Flash |
| Context window | 262K tokens | 16K tokens | INLing 3.0 Flash |
| Input price | $0.02/M · free self-host | $0.5/M | INLing 3.0 Flash |
| Output price | $0.06/M · free self-host | $1.5/M | INLing 3.0 Flash |
| Vision / multimodal | No | No | – |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | INLing 3.0 Flash |
| License | Open weights | Proprietary | INLing 3.0 Flash |
Ling 3.0 Flash is ~25× cheaper than GPT-3.5 Turbo on output tokens ($0.06 vs $1.5 per M tokens).
| Capability | Ling 3.0 Flash | GPT-3.5 Turbo |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✗ | ✗ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✗ | ✗ |
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
| Criterion | Ling 3.0 Flash | GPT-3.5 Turbo |
|---|---|---|
| Cost-efficiency | 5.0 | 4.5 |
| Context window | 4.0 | 2.0 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 3.5 | 3.5 |
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.
*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
GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks. Training data up to Sep 2021.
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Ling 3.0 Flash is open-weight and competitive on many tasks, but GPT-3.5 Turbo may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.
Yes. Ling 3.0 Flash has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. GPT-3.5 Turbo is API-only and cannot be self-hosted.
Ling 3.0 Flash costs $0.06/M output vs $1.5/M for GPT-3.5 Turbo — roughly 25x cheaper via API, and free if you self-host.
Choose Ling 3.0 Flash 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-3.5 Turbo if you want frontier capability through a managed API with zero infrastructure to run.
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