Gemini 2.0 Flash-Lite vs Llama-3.2-11B-Vision-Instruct vs Nemotron Mini 4B Instruct
Gemini 2.0 Flash-Lite comes out ahead, 72 to 40 and 25 on our weighted score, and it is the cheaper option too.
- Our pick
GoogleGemini 2.0 Flash-Lite
72/100- ECI—
- Price$0.064 / $0.255
- Context1.05M
MetaLlama-3.2-11B-Vision-Instruct
40/100- ECI—
- Price$0.055 / $0.345
- Context128K
NVIDIANemotron Mini 4B Instruct
25/100- ECI—
- Price—
- Context128K
Gemini 2.0 Flash-Lite is our pick
Gemini 2.0 Flash-Lite is the better all-round choice, scoring 72/100 against Llama-3.2-11B-Vision-Instruct (40) and Nemotron Mini 4B Instruct (25). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. 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 per 1M tokens (3:1 blend) · Nemotron Mini 4B Instruct unpriced
- Longest contextGemini 2.0 Flash-LiteGemini 2.0 Flash-Lite 1,048,576 · Llama-3.2-11B-Vision-Instruct 128,000 · Nemotron Mini 4B Instruct 128,000 tokens
- Widest inputsGemini 2.0 Flash-LiteGemini 2.0 Flash-Lite: Text, Images, PDFs, Audio, Video · Llama-3.2-11B-Vision-Instruct: Text, Images · Nemotron Mini 4B Instruct: Text
- Self-hostingLlama-3.2-11B-Vision-Instruct and Nemotron Mini 4B InstructPublishes downloadable weights
| Measure | Weight | Gemini 2.0 Flash-Lite | Llama-3.2-11B-Vision-Instruct | Nemotron Mini 4B Instruct |
|---|---|---|---|---|
| Inputs & features | 60% | 80 | 50 | 25 |
| Context window | 40% | 61 | 24 | 24 |
| Overall | 100% | 72/100 | 40/100 | 25/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 2.0 Flash-LiteGoogle | Llama-3.2-11B-Vision-InstructMeta | Nemotron Mini 4B InstructNVIDIA |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.064 | $0.055 (best) | — |
| Output | $0.255 (best) | $0.345 | — |
| Cached input | — | — | — |
| Blended (3:1) | $0.111 (best) | $0.128 | — |
| Long-context rate | Same rate | Same rate | — |
| Price source | Median of 2 providers | Median of 3 providers | — |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 128,000 tokens | 128,000 tokens |
| Max output | 8,192 tokens (best) | 4,096 tokens | 8,192 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | — | — | — |
| API providers | 3 | 4 (best) | — |
| Released | Dec 11, 2024 | Sep 25, 2024 | Aug 21, 2024 |
| Knowledge cutoff | Jun 2024 | Dec 2023 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 2.0 Flash-Lite$1.15
- Llama-3.2-11B-Vision-Instruct$1.24
- Nemotron Mini 4B Instruct—
Which should you choose?
Which is better: Gemini 2.0 Flash-Lite, Llama-3.2-11B-Vision-Instruct or Nemotron Mini 4B Instruct?
Gemini 2.0 Flash-Lite is the better all-round choice, scoring 72/100 against Llama-3.2-11B-Vision-Instruct (40) and Nemotron Mini 4B Instruct (25). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Gemini 2.0 Flash-Lite, Llama-3.2-11B-Vision-Instruct or Nemotron Mini 4B Instruct?
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). 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). Nemotron Mini 4B Instruct has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 2.0 Flash-Lite has not been scored yet, Llama-3.2-11B-Vision-Instruct has not been scored yet and Nemotron Mini 4B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.0 Flash-Lite, Llama-3.2-11B-Vision-Instruct and Nemotron Mini 4B Instruct 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 128,000 for Nemotron Mini 4B Instruct. Maximum output per response: Gemini 2.0 Flash-Lite up to 8,192, Llama-3.2-11B-Vision-Instruct up to 4,096, Nemotron Mini 4B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.0 Flash-Lite accepts text, images, PDFs, audio and video; Llama-3.2-11B-Vision-Instruct accepts text and images; Nemotron Mini 4B Instruct accepts text. Gemini 2.0 Flash-Lite handles the widest range of inputs.
Are any of these open source?
Llama-3.2-11B-Vision-Instruct and Nemotron Mini 4B Instruct publishes its weights and can be self-hosted; Gemini 2.0 Flash-Lite is proprietary.
Which is newer?
Gemini 2.0 Flash-Lite is the newest, released Dec 11, 2024. Llama-3.2-11B-Vision-Instruct came out Sep 25, 2024; Nemotron Mini 4B Instruct came out Aug 21, 2024. Knowledge cutoff: Gemini 2.0 Flash-Lite Jun 2024, Llama-3.2-11B-Vision-Instruct Dec 2023.
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.
