Gemini 3.1 Flash Lite Preview: Price, Context, Benchmarks, and Release Details
42.6
SI Score (method si-v3-retained-evidence-2)
48% confidence 48 percent, Low confidence — 2 of 7 expected sources in
Coverage 38% of expected source weight · 100% confidence at 80% coverage
Pillar breakdown
Coding (weight 40 percent) —
Math (weight 15 percent) —
Preference (weight 15 percent) 74.6
Reasoning (weight 30 percent) 8.6
Pillar weights: reasoning 30% · math 15% · coding 40% · preference 15%. Benchmark results use fixed 0–100 scales before averaging; incomplete evidence is shrunk toward 50.
Facts
- Input price / 1M
- $0.25LiteLLMFirst-party API Standard token rate; MIT LiteLLM transcription. Provider documentation: https://ai.google.dev/gemini-api/docs/pricing. Exact endpoint only; cache/batch/long-context rates excluded
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Output price / 1M
- $1.50LiteLLMFirst-party API Standard token rate; MIT LiteLLM transcription. Provider documentation: https://ai.google.dev/gemini-api/docs/pricing. Exact endpoint only; cache/batch/long-context rates excluded
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Context window
- 1Mmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Max output
- 65.5Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Released
- Mar 3, 2026models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Open weights
- Nomodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - License
- not yet reported
- Input modalities
- text, image, video, audio, pdfmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗
Benchmark results
2 results| Benchmark | Raw result | Normalized (0–100) | Pillar |
|---|---|---|---|
| hle scale | 8.6%Humanity’s Last ExamPotential contamination warning: This model was evaluated after the public release of HLE, allowing model builder access to the prompts and solutions. [variant] Published Mar 23, 2026
Retrieved Oct 9, 2026 · factual citation Open source ↗ | 8.6 | reasoning |
| lmarena text | 1415.7 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 2, 2026
Retrieved Oct 9, 2026 · CC-BY-4.0 Open source ↗ | 74.6 | preference |
Normalization uses fixed absolute 0–100 scales for each unit, independently of other models that have a result on each benchmark. Coverage and evidence breadth still affect the composite; compare the evaluation conditions before reading a small score gap as decisive. “lab-reported” marks the provider's own published figure.
Sources: in and pending
in Reported (2)
- Humanity’s Last Exam · arrived Oct 8, 2026
- LMArena / Arena · arrived Oct 8, 2026
pending Awaiting (5)
- ARC Prize · carries 13% of expected weight
- Epoch AI Benchmarking · carries 25% of expected weight
- Official model cards via models.dev · carries 4% of expected weight
- LiveBench · carries 13% of expected weight
- Terminal-Bench · carries 6% of expected weight
The confidence % rises as pending sources publish. Some sources never cover some models — that is why 100% confidence arrives at 80% of expected weight, not at full coverage.