Hy3 Open vs INLing-2.6-flash Paid
Hy3 vs Ling-2.6-flash compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
Ling-2.6-flash — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$0.53 /M outputNo per-token fees if you self-host
$0.03 /M outputManaged API (no infra to run)
Hy3 vs Ling-2.6-flash specs
| Spec | Hy3 | Ling-2.6-flash | Winner |
|---|---|---|---|
| Maker | Tencent | InclusionAI | – |
| Type | Open-weight | Proprietary | |
| Context window | 262K tokens | 262K tokens | = Tie |
| Input price | $0.13/M · free self-host | $0.01/M | INLing-2.6-flash |
| Output price | $0.53/M · free self-host | $0.03/M | INLing-2.6-flash |
| Vision / multimodal | No | No | – |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | |
| License | Open weights | Proprietary |
Price gap & when to choose each
Ling-2.6-flash is ~18× cheaper than Hy3 on output tokens ($0.03 vs $0.53 per M tokens).
- You want to self-host or run on your cloud
- You prioritize data privacy & control
- You are building open or reproducible AI
- You want frontier performance through a managed API
- You want the lower output price
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | Hy3 | Ling-2.6-flash |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✗ | ✗ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✗ | ✗ |
Benchmarks: Hy3 vs Ling-2.6-flash
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How Hy3 and Ling-2.6-flash score
| Criterion | Hy3 | Ling-2.6-flash |
|---|---|---|
| Cost-efficiency | 5.0 | 5.0 |
| Context window | 4.0 | 4.0 |
| 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.
What each model is
Hy3 Open
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:...
Ling-2.6-flash Paid
Ling-2.6-flash is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency....
Other models in these families
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Frequently asked questions
Is Hy3 as good as Ling-2.6-flash?
Hy3 is open-weight and competitive on many tasks, but Ling-2.6-flash 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 Hy3 locally?
Yes. Hy3 has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Ling-2.6-flash is API-only and cannot be self-hosted.
Hy3 vs Ling-2.6-flash — which should I pick in 2026?
Choose Hy3 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 Ling-2.6-flash if you want frontier capability through a managed API with zero infrastructure to run.
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