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Comparison · 2 models · Updated Nov 2, 2026

Hy-MT2-1.8B vs Ling 3.0 Flash VL

Ling 3.0 Flash VL comes out ahead, 76 to 49 on our weighted score, though Hy-MT2-1.8B is 14% cheaper per token.

  1. Tencent

    Hy-MT2-1.8B

    Released May 21, 2026

    49/100
    • ECI—
    • Price$0.044 / $0.177
    • Context8K
  2. Our pick

    inclusionAI

    Ling 3.0 Flash VL

    Released Sep 10, 2026New

    76/100
    • ECI—
    • Price$0.06 / $0.18
    • Context262K
  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Ling 3.0 Flash VL is our pick

Ling 3.0 Flash VL is the better all-round choice, scoring 76/100 against Hy-MT2-1.8B (49). It leads on inputs & features and context window. Hy-MT2-1.8B wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceHy-MT2-1.8BHy-MT2-1.8B $0.077 · Ling 3.0 Flash VL $0.09 per 1M tokens (3:1 blend)
  • Longest contextLing 3.0 Flash VLLing 3.0 Flash VL 262,144 · Hy-MT2-1.8B 8,192 tokens
  • Widest inputsLing 3.0 Flash VLHy-MT2-1.8B: Text · Ling 3.0 Flash VL: Text, Images, Video
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightHy-MT2-1.8BLing 3.0 Flash VL
Price50%9895
Inputs & features30%070
Context window20%037
Overall100%49/10076/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Hy-MT2-1.8B vs Ling 3.0 Flash VL specifications side by side
SpecificationHy-MT2-1.8BTencentLing 3.0 Flash VLinclusionAI
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.044 (best)$0.06
Output$0.177 (best)$0.18
Cached input——
Blended (3:1)$0.077 (best)$0.09
Long-context rateSame rateSame rate
Price sourceMedian of 3 providersMedian of 7 providers
Limits
Context window8,192 tokens262,144 tokens (best)
Max output4,096 tokens32,768 tokens (best)
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoNo
AudioNoNo
VideoNoYes
ReasoningNoYes
Tool callingNoYes
Structured outputNoNo
Availability
WeightsOpenOpenMIT
API model ID——
API providers37 (best)
ReleasedMay 21, 2026Sep 10, 2026
Knowledge cutoff——
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Hy-MT2-1.8B$0.794
  • Ling 3.0 Flash VL$0.96
04 — Questions

Which should you choose?

Which is better: Hy-MT2-1.8B or Ling 3.0 Flash VL?

Ling 3.0 Flash VL is the better all-round choice, scoring 76/100 against Hy-MT2-1.8B (49). It leads on inputs & features and context window. Hy-MT2-1.8B wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Hy-MT2-1.8B or Ling 3.0 Flash VL?

Hy-MT2-1.8B is cheaper at $0.044 input / $0.177 output per million tokens (median across 3 API providers). Ling 3.0 Flash VL costs $0.06 input / $0.18 output per million tokens (median across 7 API providers). At a typical mix of three input tokens to one output token, that is $0.077 per million tokens for Hy-MT2-1.8B versus $0.09 for Ling 3.0 Flash VL (1.2× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Hy-MT2-1.8B has not been scored yet and Ling 3.0 Flash VL has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Hy-MT2-1.8B and Ling 3.0 Flash VL yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Hy-MT2-1.8B does not support tool calling, which most coding agents need.

Which has the bigger context window?

Ling 3.0 Flash VL has the largest context window at 262,144 tokens, against 8,192 for Hy-MT2-1.8B. Maximum output per response: Hy-MT2-1.8B up to 4,096, Ling 3.0 Flash VL up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Hy-MT2-1.8B accepts text; Ling 3.0 Flash VL accepts text, images and video. Ling 3.0 Flash VL handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights (MIT), so you can self-host them.

Which is newer?

Ling 3.0 Flash VL is the newest, released Sep 10, 2026. Hy-MT2-1.8B came out May 21, 2026.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.