Skip to content
Sign in

Gemini 3.1 Flash Lite vs Llama 4 Scout

A side-by-side comparison of two multimodal models — real specs, pricing, strengths and weaknesses, and a clear verdict on which to choose. Kept current by our agents.

Quick verdict: which should you choose?

Choose Gemini 3.1 Flash Lite if you need

  • Need an extremely large 10M token context for long text and image sequences
  • Require open-weight access and lowest price at $0.3 per million tokens
  • Prioritize strong reasoning over extended multimodal inputs
  • Can tolerate slower 109 t/s speeds for maximum context scale

Choose Llama 4 Scout if you need

  • Demand highest output speed at 271 t/s with low latency
  • Need higher intelligence index of 25 and broad text/image/video support
  • Prefer resource-efficient inference in a lightweight proprietary package
  • Work within a 1M token context while valuing overall responsiveness

Verdict

Llama 4 Scout leads for maximum context scale and cost efficiency with its 10M token window and $0.3/M pricing, while Gemini 3.1 Flash Lite dominates speed and intelligence with 271 t/s output and index of 25. Llama suits long-sequence multimodal reasoning under open weights; Gemini excels in fast, resource-efficient inference across broader modalities. Neither model sweeps all metrics, creating a clear split between scale-focused and performance-focused use cases.

Gemini 3.1 Flash Lite vs Llama 4 Scout: side by side

SpecGemini 3.1 Flash LiteLlama 4 ScoutWinner
Intelligence2510Gemini 3.1 Flash Lite
Output speed280 t/s111 t/sGemini 3.1 Flash Lite
Output price$1.50/1M$0.30/1MLlama 4 Scout
Context1049K10000KLlama 4 Scout
ParamsTie
ProviderGoogleMetaTie

Detailed analysis

Intelligence

Winner: Gemini 3.1 Flash Lite

Gemini 3.1 Flash Lite scores 25 on the intelligence index compared to Llama 4 Scout's 10. This gives Gemini an edge on complex tasks despite its lite design. Llama's lower score aligns with its focus on long-context handling rather than peak capability.

Speed

Winner: Gemini 3.1 Flash Lite

Gemini 3.1 Flash Lite achieves 271.14 tokens per second versus Llama 4 Scout's 109.63 t/s. The speed advantage supports Gemini's strength in low-latency scenarios. Llama may show latency on very long sequences as noted in its limitations.

Context Window & Cost

Winner: Llama 4 Scout

Llama 4 Scout offers a 10M token context at $0.3 per million tokens, far exceeding Gemini's 1M context and $1.5 price. This makes Llama preferable for large-scale inputs where cost efficiency matters. Gemini still handles very large contexts but at higher cost and smaller maximum length.

Modality Support

Winner: Gemini 3.1 Flash Lite

Gemini 3.1 Flash Lite provides broad modality support including video in a lightweight package. Llama 4 Scout is limited to native text and image inputs only. This gives Gemini wider applicability for diverse multimodal tasks.

Gemini 3.1 Flash Lite

Pros

  • +High speed and low latency
  • +Handles very large context windows
  • +Broad modality support in a lightweight package

Cons

  • Reduced depth on highly complex reasoning tasks
  • Lite design trades peak capability for speed
  • May require more guidance on nuanced or creative outputs
Full Gemini 3.1 Flash Lite review →

Llama 4 Scout

Pros

  • +Extremely large context window
  • +Native multimodal input support
  • +Strong reasoning over long inputs

Cons

  • High compute cost at maximum context
  • Limited to text and image modalities only
  • May exhibit latency on very long sequences
Full Llama 4 Scout review →

Summary: Gemini 3.1 Flash Lite vs Llama 4 Scout

Choose Llama 4 Scout when maximum context length, open weights, and lower cost are primary needs for long text-image sequences. Select Gemini 3.1 Flash Lite for superior speed, higher intelligence scores, and broader modality coverage in efficient inference. The models target different priorities within multimodal workloads.

Frequently asked questions

It depends on priorities: Llama 4 Scout for largest context and lowest cost, Gemini 3.1 Flash Lite for speed and intelligence.

More ai model comparisons