Google, released Jun 17, 2025

Gemini 2.5 Flashprice, context, benchmarks and release details

Provisional: not enough results to rank yet 47% confidence 47 percent, Low confidence, 3 of 8 expected sources in
45.0
SI Score
Not ranked yet
Input, per 1M tokens
$0.30Google Gemini pricingOfficial paid Standard text rate, lowest short-context tier; current promotional price if dated; excludes free/Batch/Flex/audio Retrieved Oct 9, 2026 · CC-BY-4.0 factual citation
Open source ↗
Output, per 1M tokens
$2.50Google Gemini pricingOfficial paid Standard text rate, lowest short-context tier; current promotional price if dated; excludes free/Batch/Flex/audio Retrieved Oct 9, 2026 · CC-BY-4.0 factual citation
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
Jun 17, 2025Google Gemini release notesPublished source fact Retrieved Oct 9, 2026 · CC-BY-4.0 factual citation
Open source ↗

How the score breaks down

Coding (weight 40 percent) 22.5
Math (weight 15 percent) —
Preference (weight 15 percent) 74.7
Reasoning (weight 30 percent) —

Weights: reasoning 30%, math 15%, coding 40%, preference 15%. Results use fixed 0–100 scales before averaging, and thin evidence is pulled toward 50. Method si-v3-retained-evidence-2, computed Oct 9, 2026, 06:15 UTC.

Around it on the leaderboard

  1. 1 Claude Fable 5.1 80.2
  2. 2 Claude Opus 5.5 78.4
  3. 3 GPT-6 Astra 77.5
  4. 4 Claude Fable 5 76.8
  5. 5 Claude Opus 5 74.9

Full leaderboard

Benchmark results

3 benchmarks, 3 results

Each row shows the best published result. Where a model was tested at several settings, such as reasoning effort, open the row to see each one. Hover or tap a value for its source.

SWE-bench Verifiedcoding 28.7%SWE-bench VerifiedSWE-bench published model plus agent result; harness retained, not a base model evaluation [variant] mini-SWE-agent; 1.0.0Published Jul 26, 2025 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 28.7
Terminal-Benchcoding 13.6%Official model cards via models.devLab-reported; metric success rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] Published Jun 2, 2026 Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗ 13.6
LMArena Textpreference 1416.9 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 8, 2026 Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗ 74.7

Normalization uses a fixed 0–100 scale for each unit, independent of other models. Compare evaluation conditions before reading a small gap as decisive. “Lab-reported” marks the provider's own published figure.

Details and sources

Open weights
Nomodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
License
not yet reported
Input modalities
text, image, audio, video, pdfmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
First seen by SuperIndex
Oct 8, 2026
Coverage
38% of expected source weight

Reported (3)

  • Official model cards via models.devOct 8, 2026
  • LMArena / ArenaOct 8, 2026
  • SWE-bench VerifiedOct 8, 2026

Awaiting (5)

  • ARC Prize11% of weight
  • Epoch AI Benchmarking23% of weight
  • Humanity’s Last Exam11% of weight
  • LiveBench11% of weight
  • Terminal-Bench6% of weight

Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.

What changed

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