Granite 4.2 8B vs Ling 3.0 Flash Sante 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.
IBMGranite 4.2 8B
64/100- ECI—
- Price$0.06 / $0.15
- Context131K
inclusionAILing 3.0 Flash Sante
63/100- ECI—
- Price$0.075 / $0.22
- Context262K
- Our pickinclusionAI
Ling 3.0 Flash VL
76/100- ECI—
- Price$0.06 / $0.18
- Context262K
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 Sante (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 Sante $0.111 per 1M tokens (3:1 blend)
- Longest contextLing 3.0 Flash Sante and Ling 3.0 Flash VLLing 3.0 Flash Sante 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 Sante: Text · Ling 3.0 Flash VL: Text, Images, Video
- Self-hostingGranite 4.2 8B and Ling 3.0 Flash VLPublishes downloadable weights (MIT)
| Measure | Weight | Granite 4.2 8B | Ling 3.0 Flash Sante | Ling 3.0 Flash VL |
|---|---|---|---|---|
| Price | 50% | 97 | 91 | 95 |
| Inputs & features | 30% | 35 | 35 | 70 |
| Context window | 20% | 25 | 37 | 37 |
| Overall | 100% | 64/100 | 63/100 | 76/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Granite 4.2 8BIBM | Ling 3.0 Flash SanteinclusionAI | Ling 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 rate | Same rate | Same rate | Same rate |
| Price source | Median of 7 providers | Median of 2 providers | Median of 7 providers |
| Limits | |||
| Context window | 131,072 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 117,964 tokens (best) | 32,768 tokens | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | OpenMIT |
| API model ID | — | — | — |
| API providers | 7 (best) | 2 | 7 (best) |
| Released | Aug 25, 2026 | Sep 4, 2026 | Sep 10, 2026 |
| Knowledge cutoff | — | — | — |
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 Sante$1.19
- Ling 3.0 Flash VL$0.96
Which should you choose?
Which is better: Granite 4.2 8B, Ling 3.0 Flash Sante 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 Sante (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 Sante 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 Sante 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 Sante (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 Sante 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 Sante 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 Sante 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 Sante 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 Sante 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?
Granite 4.2 8B and Ling 3.0 Flash VL publishes its weights (MIT) and can be self-hosted; Ling 3.0 Flash Sante is proprietary.
Which is newer?
Ling 3.0 Flash VL is the newest, released Sep 10, 2026. Ling 3.0 Flash Sante came out Sep 4, 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.
