Gemini 3.8 Flash
Google's most capable Flash model, aimed at long-horizon coding, agents and enterprise workflows at Flash speed and cost. It sits just behind the leaders on the LMArena text leaderboard and ties for first on LMArena Vision.
GoogleLanguage modelReleased September 2026Data checked October 18, 2026
This model is not in the current people's rankings: it is either new and still collecting votes, or ranked below the top 12. See the AI leaderboard for the models people rate highest.
On paper
Fixed-test rankings from the benchmarks tab: Speed #4, Value #5, Reasoning #10.
Strengths and weaknesses
- Just behind the leaders on the LMArena text leaderboard, ahead of every OpenAI model
- Tied for first on LMArena Vision and 95.3% on GPQA Diamond (Artificial Analysis)
- Fast output (147 tokens per second) and 89.2% on ARC-AGI-2
- Weak at agentic terminal tasks (19.1% on Terminal-Bench 4.0)
- The current $0.75 / $3.75 per million price doubles to $1.50 / $7.50 on January 1, 2027
Best for
- A fast everyday assistant
- Understanding images, video and PDFs
- Good quality at a low price
Every score we have
Each bar compares this model with the best result any model on this page has on the same test.
- LMArena text arena (human votes)1,496.4Arena score 1496.4 (95% CI 1491.8 to 1501.0); 37,454 votes; entry "Gemini 3.8 Flash (High)"; position 9 of 416 on the full board
- LMArena creative writing1,486.9Arena score 1486.9 (95% CI 1479.0 to 1494.9); 8,232 votes; entry "Gemini 3.8 Flash (High)"; position 7 of 414 on the full board
- LMArena WebDev (coding)1,585.2Arena score 1585.2 (95% CI 1577.7 to 1592.7); 10,514 votes; entry "Gemini 3.8 Flash (High)"; position 31 of 144 on the full board
- LMArena vision1,289.1Arena score 1289.1 (95% CI 1278.5 to 1299.7); 3,792 votes; entry "gemini-3.8-flash-high"; position 14 of 165 on the full board
- LMArena Agent Arena0.037IPS score 0.0375 (95% CI 0.0265 to 0.0485); 37,692 sessions; entry "Gemini 3.8 Flash (High)"; position 15 of 52 on the full board
- Artificial Analysis Intelligence Index40.940.9 on the Artificial Analysis Intelligence Index v4.3.2 (AA shows 41), setting "Gemini 3.8 Flash (high)"
- Humanity's Last Exam (Artificial Analysis)47.8%47.8% on Humanity's Last Exam (AA, 2,158 text-only questions), setting "Gemini 3.8 Flash (high)"
- GPQA Diamond, graduate-level science95.3%95.3% on GPQA Diamond (AA; no longer part of the AA index since v4.2), setting "Gemini 3.8 Flash (high)"
- Terminal-Bench 4.0 (Artificial Analysis run)19.7%19.7% on Terminal-Bench 4.0 as run by AA (mini-swe-agent harness), setting "Gemini 3.8 Flash (high)"
- Long-context reasoning (AA-LCR)81.3%81.3% on AA-LCR (long-context reasoning), setting "Gemini 3.8 Flash (high)"
- MMMU-Pro, image understanding85.6%85.6% on MMMU-Pro (image understanding, AA), setting "Gemini 3.8 Flash (high)"
- AA-Omniscience, accuracy minus hallucination29.629.6 on the AA-Omniscience Index (knowledge accuracy minus hallucination, range -100 to 100), setting "Gemini 3.8 Flash (high)"
- Output speed, tokens per second147 t/s147 output tokens per second (AA median), row "Gemini 3.8 Flash (high)"
- Cost per Artificial Analysis test task$1.24$1.24 to run one AA Intelligence Index task, row "Gemini 3.8 Flash (high)"
- Artificial Analysis Coding Agent Index41.941.9 on the AA Coding Agent Index v1.5 (DeepSWE v1.1, Terminal-Bench 4.0, SWE-Atlas-QnA), best listed setup "Antigravity SDK - Gemini 3.8 Flash (high)"
- Terminal-Bench 4.0 leaderboard19.1%19.1% resolved on Terminal-Bench 4.0 (plus or minus 3.4, 95% CI) with mini-SWE-agent at high effort
- ARC-AGI-2 puzzles89.2%89.17% on ARC-AGI-2 (semi-private set), best listed setting "Gemini 3.8 Flash (High)", $0.40 per task
- ARC-AGI-3 puzzles10.4%10.37% on ARC-AGI-3 (semi-private, standard harness; "provider adapter" runs excluded), best listed setting "Gemini 3.8 Flash (High)"
- Humanity's Last Exam (Scale AI)44.5%44.52% on Scale AI's Humanity's Last Exam leaderboard (plus or minus 1.96), entry "Gemini 3.8 Flash"
Compare with
- Claude Opus 5.5Anthropic's flagship for long-running agentic coding and knowledge work, and the model Anthropic suggests starting with for most jobs.
- Claude Sonnet 5.5Anthropic's mid-priced model, which Anthropic describes as its best mix of speed and intelligence.
- Claude Fable 5.1Anthropic's top tier for the hardest reasoning and long-horizon agent work, which Anthropic recommends when Opus 5.5 still falls short.
- Claude Haiku 5.5Anthropic's smallest and fastest current model, built for high-volume, latency-sensitive jobs like classification, extraction and routing.