ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Granite 4.2 8B vs Ling 3.0 Flash Fin vs Ling 3.0 Flash VL

Ling 3.0 Flash VL comes out ahead, 76 to 64 and 63 on our weighted score, though Granite 4.2 8B is 8% cheaper per token.

  1. IBM

    Granite 4.2 8B

    Released Aug 25, 2026

    64/100
    • ECI—
    • Price$0.06 / $0.15
    • Context131K
  2. inclusionAI

    Ling 3.0 Flash Fin

    Released Aug 27, 2026

    63/100
    • ECI—
    • Price$0.075 / $0.22
    • Context262K
  3. Our pick

    inclusionAI

    Ling 3.0 Flash VL

    Released Sep 10, 2026New

    76/100
    • ECI—
    • Price$0.06 / $0.18
    • Context262K
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 Granite 4.2 8B (64) and Ling 3.0 Flash Fin (63). It leads on inputs & features. Granite 4.2 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 priceGranite 4.2 8BGranite 4.2 8B $0.083 · Ling 3.0 Flash VL $0.09 · Ling 3.0 Flash Fin $0.111 per 1M tokens (3:1 blend)
  • Longest contextLing 3.0 Flash Fin and Ling 3.0 Flash VLLing 3.0 Flash Fin 262,144 · Ling 3.0 Flash VL 262,144 · Granite 4.2 8B 131,072 tokens
  • Widest inputsLing 3.0 Flash VLGranite 4.2 8B: Text · Ling 3.0 Flash Fin: 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
MeasureWeightGranite 4.2 8BLing 3.0 Flash FinLing 3.0 Flash VL
Price50%979195
Inputs & features30%353570
Context window20%253737
Overall100%64/10063/10076/100

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.

Granite 4.2 8B vs Ling 3.0 Flash Fin vs Ling 3.0 Flash VL specifications side by side
SpecificationGranite 4.2 8BIBMLing 3.0 Flash FininclusionAILing 3.0 Flash VLinclusionAI
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.06 (best)$0.075$0.06 (best)
Output$0.15 (best)$0.22$0.18
Cached input———
Blended (3:1)$0.083 (best)$0.111$0.09
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 7 providersMedian of 2 providersMedian of 7 providers
Limits
Context window131,072 tokens262,144 tokens (best)262,144 tokens (best)
Max output117,964 tokens (best)32,768 tokens32,768 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoYes
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenMITOpenMIT
API model ID———
API providers7 (best)37 (best)
ReleasedAug 25, 2026Aug 27, 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.

  • Granite 4.2 8B$0.90
  • Ling 3.0 Flash Fin$1.19
  • Ling 3.0 Flash VL$0.96
04 — Questions

Which should you choose?

Which is better: Granite 4.2 8B, Ling 3.0 Flash Fin or Ling 3.0 Flash VL?

Ling 3.0 Flash VL is the better all-round choice, scoring 76/100 against Granite 4.2 8B (64) and Ling 3.0 Flash Fin (63). It leads on inputs & features. Granite 4.2 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, Granite 4.2 8B, Ling 3.0 Flash Fin or Ling 3.0 Flash VL?

Granite 4.2 8B is cheaper at $0.06 input / $0.15 output per million tokens (median across 7 API providers). Ling 3.0 Flash VL costs $0.06 input / $0.18 output per million tokens (median across 7 API providers); Ling 3.0 Flash Fin costs $0.075 input / $0.22 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.083 per million tokens for Granite 4.2 8B versus $0.09 for Ling 3.0 Flash VL (1.1× as much) and $0.111 for Ling 3.0 Flash Fin (1.3× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Granite 4.2 8B has not been scored yet, Ling 3.0 Flash Fin 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 Granite 4.2 8B, Ling 3.0 Flash Fin 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. All three support tool calling for agent workflows.

Which has the bigger context window?

Ling 3.0 Flash Fin and Ling 3.0 Flash VL have the largest context windows (262,144 and 262,144 tokens), against 131,072 for Granite 4.2 8B. Maximum output per response: Granite 4.2 8B up to 117,964, Ling 3.0 Flash Fin up to 32,768, Ling 3.0 Flash VL up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Granite 4.2 8B accepts text; Ling 3.0 Flash Fin 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, all three 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. Ling 3.0 Flash Fin came out Aug 27, 2026; Granite 4.2 8B came out Aug 25, 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.