Gemini 2.5 Flash-Lite vs GLM-4.5-Air vs Llama 3.3 Nemotron Super 49B v1.5
Gemini 2.5 Flash-Lite comes out ahead, 83 to 48 and 48 on our weighted score, and it is the cheaper option too.
- Our pick
GoogleGemini 2.5 Flash-Lite
83/100- ECI—
- Price$0.10 / $0.40
- Context1.05M
Z.ai (Zhipu)GLM-4.5-Air
48/100- ECI—
- Price$0.20 / $1.10
- Context131K
NVIDIALlama 3.3 Nemotron Super 49B v1.5
48/100- ECI—
- Price$0.40 / $0.40
- Context131K
Gemini 2.5 Flash-Lite is our pick
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 83/100 against Llama 3.3 Nemotron Super 49B v1.5 (48) and GLM-4.5-Air (48). 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 2.5 Flash-LiteGemini 2.5 Flash-Lite $0.175 · Llama 3.3 Nemotron Super 49B v1.5 $0.40 · GLM-4.5-Air $0.425 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · GLM-4.5-Air 131,072 · Llama 3.3 Nemotron Super 49B v1.5 131,072 tokens
- Widest inputsGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · GLM-4.5-Air: Text · Llama 3.3 Nemotron Super 49B v1.5: Text
- Self-hostingGLM-4.5-Air and Llama 3.3 Nemotron Super 49B v1.5Publishes downloadable weights
| Measure | Weight | Gemini 2.5 Flash-Lite | GLM-4.5-Air | Llama 3.3 Nemotron Super 49B v1.5 |
|---|---|---|---|---|
| Price | 50% | 82 | 65 | 66 |
| Inputs & features | 30% | 100 | 35 | 35 |
| Context window | 20% | 61 | 25 | 25 |
| Overall | 100% | 83/100 | 48/100 | 48/100 |
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 | Gemini 2.5 Flash-LiteGoogle | GLM-4.5-AirZ.ai (Zhipu) | Llama 3.3 Nemotron Super 49B v1.5NVIDIA |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.10 (best) | $0.20 | $0.40 |
| Output | $0.40 (best) | $1.10 | $0.40 (best) |
| Cached input | $0.01 (best) | $0.03 | — |
| Blended (3:1) | $0.175 (best) | $0.425 | $0.40 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Google API | Official Z.AI API | Median of 1 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 131,072 tokens | 131,072 tokens |
| Max output | 65,536 tokens | 98,304 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | gemini-2.5-flash-lite | glm-4.5-air | — |
| API providers | 24 (best) | 19 | 1 |
| Released | Jun 17, 2025 | Jul 28, 2025 | Jul 25, 2025 |
| Knowledge cutoff | Jan 2025 | Apr 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 2.5 Flash-Lite$1.80
- GLM-4.5-Air$4.20
- Llama 3.3 Nemotron Super 49B v1.5$4.80
Which should you choose?
Which is better: Gemini 2.5 Flash-Lite, GLM-4.5-Air or Llama 3.3 Nemotron Super 49B v1.5?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 83/100 against Llama 3.3 Nemotron Super 49B v1.5 (48) and GLM-4.5-Air (48). 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, Gemini 2.5 Flash-Lite, GLM-4.5-Air or Llama 3.3 Nemotron Super 49B v1.5?
Gemini 2.5 Flash-Lite is cheaper at $0.10 input / $0.40 output per million tokens (official Google API price). Llama 3.3 Nemotron Super 49B v1.5 costs $0.40 input / $0.40 output per million tokens (median across 1 API provider); GLM-4.5-Air costs $0.20 input / $1.10 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for Gemini 2.5 Flash-Lite versus $0.40 for Llama 3.3 Nemotron Super 49B v1.5 (2.3× as much) and $0.425 for GLM-4.5-Air (2.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 2.5 Flash-Lite has not been scored yet, GLM-4.5-Air has not been scored yet and Llama 3.3 Nemotron Super 49B v1.5 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.5 Flash-Lite, GLM-4.5-Air and Llama 3.3 Nemotron Super 49B v1.5 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 2.5 Flash-Lite has the largest context window at 1,048,576 tokens, against 131,072 for GLM-4.5-Air and 131,072 for Llama 3.3 Nemotron Super 49B v1.5. Maximum output per response: Gemini 2.5 Flash-Lite up to 65,536, GLM-4.5-Air up to 98,304, Llama 3.3 Nemotron Super 49B v1.5 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; GLM-4.5-Air accepts text; Llama 3.3 Nemotron Super 49B v1.5 accepts text. Gemini 2.5 Flash-Lite handles the widest range of inputs.
Are any of these open source?
GLM-4.5-Air and Llama 3.3 Nemotron Super 49B v1.5 publishes its weights and can be self-hosted; Gemini 2.5 Flash-Lite is proprietary.
Which is newer?
GLM-4.5-Air is the newest, released Jul 28, 2025. Llama 3.3 Nemotron Super 49B v1.5 came out Jul 25, 2025; Gemini 2.5 Flash-Lite came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 2025, GLM-4.5-Air Apr 2025.
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.
