Llama-3.2-11B-Vision-Instruct vs Saba vs Gemini 2.0 Flash-Lite
Gemini 2.0 Flash-Lite comes out ahead, 82 to 64 and 46 on our weighted score, and it is the cheaper option too.
MetaLlama-3.2-11B-Vision-Instruct
64/100- ECI—
- Price$0.055 / $0.345
- Context128K
Mistral AISaba
46/100- ECI—
- Price$0.20 / $0.60
- Context33K
- Our pick
GoogleGemini 2.0 Flash-Lite
82/100- ECI—
- Price$0.064 / $0.255
- Context1.05M
Gemini 2.0 Flash-Lite is our pick
Gemini 2.0 Flash-Lite is the better all-round choice, scoring 82/100 against Llama-3.2-11B-Vision-Instruct (64) and Saba (46). It leads on price, inputs & features and context window. 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 priceGemini 2.0 Flash-LiteGemini 2.0 Flash-Lite $0.111 · Llama-3.2-11B-Vision-Instruct $0.128 · Saba $0.30 per 1M tokens (3:1 blend)
- Longest contextGemini 2.0 Flash-LiteGemini 2.0 Flash-Lite 1,048,576 · Llama-3.2-11B-Vision-Instruct 128,000 · Saba 32,768 tokens
- Widest inputsGemini 2.0 Flash-LiteLlama-3.2-11B-Vision-Instruct: Text, Images · Saba: Text, PDFs · Gemini 2.0 Flash-Lite: Text, Images, PDFs, Audio, Video
- Self-hostingLlama-3.2-11B-Vision-InstructPublishes downloadable weights
| Measure | Weight | Llama-3.2-11B-Vision-Instruct | Saba | Gemini 2.0 Flash-Lite |
|---|---|---|---|---|
| Price | 50% | 88 | 72 | 91 |
| Inputs & features | 30% | 50 | 35 | 80 |
| Context window | 20% | 24 | 0 | 61 |
| Overall | 100% | 64/100 | 46/100 | 82/100 |
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 | Llama-3.2-11B-Vision-InstructMeta | SabaMistral AI | Gemini 2.0 Flash-LiteGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.055 (best) | $0.20 | $0.064 |
| Output | $0.345 | $0.60 | $0.255 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.128 | $0.30 | $0.111 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 4 providers | Median of 2 providers |
| Limits | |||
| Context window | 128,000 tokens | 32,768 tokens | 1,048,576 tokens (best) |
| Max output | 4,096 tokens | 26,214 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | — | — | — |
| API providers | 4 (best) | 4 (best) | 3 |
| Released | Sep 25, 2024 | Feb 17, 2025 | Dec 11, 2024 |
| Knowledge cutoff | Dec 2023 | Sep 30, 2024 | Jun 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Llama-3.2-11B-Vision-Instruct$1.24
- Saba$3.20
- Gemini 2.0 Flash-Lite$1.15
Which should you choose?
Which is better: Llama-3.2-11B-Vision-Instruct, Saba or Gemini 2.0 Flash-Lite?
Gemini 2.0 Flash-Lite is the better all-round choice, scoring 82/100 against Llama-3.2-11B-Vision-Instruct (64) and Saba (46). It leads on price, inputs & features and context window. 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, Llama-3.2-11B-Vision-Instruct, Saba or Gemini 2.0 Flash-Lite?
Gemini 2.0 Flash-Lite is cheaper at $0.064 input / $0.255 output per million tokens (median across 2 API providers). Llama-3.2-11B-Vision-Instruct costs $0.055 input / $0.345 output per million tokens (median across 3 API providers); Saba costs $0.20 input / $0.60 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $0.111 per million tokens for Gemini 2.0 Flash-Lite versus $0.128 for Llama-3.2-11B-Vision-Instruct (1.1× as much) and $0.30 for Saba (2.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Llama-3.2-11B-Vision-Instruct has not been scored yet, Saba has not been scored yet and Gemini 2.0 Flash-Lite has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-11B-Vision-Instruct, Saba and Gemini 2.0 Flash-Lite 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?
Gemini 2.0 Flash-Lite has the largest context window at 1,048,576 tokens, against 128,000 for Llama-3.2-11B-Vision-Instruct and 32,768 for Saba. Maximum output per response: Llama-3.2-11B-Vision-Instruct up to 4,096, Saba up to 26,214, Gemini 2.0 Flash-Lite up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-11B-Vision-Instruct accepts text and images; Saba accepts text and PDFs; Gemini 2.0 Flash-Lite accepts text, images, PDFs, audio and video. Gemini 2.0 Flash-Lite handles the widest range of inputs.
Are any of these open source?
Llama-3.2-11B-Vision-Instruct publishes its weights and can be self-hosted; Saba and Gemini 2.0 Flash-Lite is proprietary.
Which is newer?
Saba is the newest, released Feb 17, 2025. Gemini 2.0 Flash-Lite came out Dec 11, 2024; Llama-3.2-11B-Vision-Instruct came out Sep 25, 2024. Knowledge cutoff: Llama-3.2-11B-Vision-Instruct Dec 2023, Saba Sep 30, 2024, Gemini 2.0 Flash-Lite Jun 2024.
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.
