Model comparison
Gemini 2.5 Pro vs Gemini 3.8 Flash
Two Google tiers compared on the figures that decide which one a workload actually needs.
Catalog record checked September 3, 2026Individual provider fields may changeEvidence confidence: High — see receipts below
Gemini 2.5 Pro
Balanced
Gemini 3.8 Flash
Balanced
| Specification | Gemini 2.5 Pro | Gemini 3.8 Flash |
|---|---|---|
| Provider | ||
| Tier | Balanced | Balanced |
| Context window | 1.05M | 1.05M |
| Max output | 66K | 66K |
| Input / 1M tokens | $1.25 | Winner: $0.75 |
| Output / 1M tokens | $10 | Winner: $3.75 |
| Weights | Closed | Closed |
| Parameters | Not disclosedUnverified | Not disclosedUnverified |
| Reasoning levels | low, medium, high | low, medium, high |
| Modalities | text, image, video, audio, pdf | text, image, video, audio, pdf |
| API model id | gemini-2.5-pro | gemini-3.8-flash |
| Released | June 17, 2025 | September 2, 2026 |
| Artificial Analysis Intelligence Index (2026-08-14) | 47 | Not verifiedUnverified |
| Artificial Analysis Intelligence Index [high] (2026-09-02) | Not verifiedUnverified | 58.7 |
| Terminal-Bench 2.1 (2026-09-02) | Not verifiedUnverified | 89.4 |
| Humanity's Last Exam (2026-09-02) | Not verifiedUnverified | 54.9 |
Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Benchmark receipts
- 2026-09-02: Google official blog (vendor, HLE-Verified full set)Frontier-knowledge ceiling: extremely hard multi-domain questions written to be near-impossible without deep expertise. Comparability: comparable with caveat — Subset/tool configurations (text-only vs with-tools) differ between vendors and materially change scores; must match configuration to compare.
- 2026-09-02: Google launch eval table (transcribed by Vellum)Agentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.
- 2026-09-02: Artificial AnalysisComposite index blending reasoning, knowledge, and coding evals into one 0–100 score. Comparability: directly comparable — AA occasionally rebaselines the index scale between snapshots — a score captured on one date is only comparable to same-snapshot scores (check measuredAt).
Pricing tiers: Gemini 2.5 Pro: $1.25/$10 per MTok (≤200K); $2.50/$15 (>200K). Legacy but still widely listed. · Gemini 3.8 Flash: Intro $0.75/$3.75 per MTok through 2026-12-31, rising to $1.50/$7.50 from 2027-01-01; batch/Flex half price. Free tier available. Companion Gemini 3.8 Flash Cyber (defensive security) is restricted to the Fairwind Program with no public pricing.
Gemini 2.5 Pro
Gemini 2.5 Pro is Google's previous-generation Pro with a 1.05M-token context and strong multimodal support.
Best for
- Long documents
- Multimodal input
- Google Workspace integration
Watch out
A generation behind Gemini 3.x; verify on your workload.
Gemini 3.8 Flash
Gemini 3.8 Flash is Google's most-intelligent workhorse Flash — tied for the top of DeepSWE 1.1 with Claude Opus 5 at roughly a fifth of the cost per task, three Flash releases in six weeks.
Best for
- Agentic coding at scale
- Mid-difficulty engineering
- Multimodal pipelines
Watch out
Intro pricing doubles on 2027-01-01, and Google says it can consume more tokens than 3.7 Flash — 3.7 Flash stays available for efficiency-first workloads.
Benchmark
DeepSWE 1.1 in context
Only Gemini 3.8 Flash has a published DeepSWE 1.1 result. It is shown against the wider field, with cost per completed task alongside the score.
Local leader
Gemini 3.8 Flash [high]
74%
Rows shown
27
Highest published reasoning effort per model (not best Pass@1)
Snapshot date
2026-09-03
Mirrored from deepswe.datacurve.ai
Better is toward the top-right (higher pass rate, lower cost). X-axis is reversed to match DeepSWE’s public chart. v1.1 uses average cost / tokens / steps; v1 uses published medians.
| # | Model | Pass@1 | Cost / task | Tokens / task | Steps / task |
|---|---|---|---|---|---|
| 1 | Gemini 3.8 Flash [high] | 74% | $2.36 | 143k | 166 |
| 2 | Claude Opus 5 [max] | 74% | $11.84 | 118k | 99 |
| 3 | GPT-5.6 Sol [max] | 73% | $8.39 | 60k | 61 |
| 4 | Claude Fable 5 [max] | 70% | $21.63 | 119k | 88 |
| 5 | GPT-5.6 Terra [max] | 70% | $4.95 | 72k | 76 |
| 6 | GLM 5.3 [max] | 69% | $3.99 | 80k | 124 |
| 7 | Kimi K3 [max] | 69% | $4.65 | 82k | 98 |
| 8 | GPT-5.6 Luna [max] | 67% | $3.03 | 73k | 102 |
| 9 | GPT-5.5 [xhigh] | 67% | $7.23 | 46k | 82 |
| 10 | Grok 4.6 [xhigh] | 67% | $5.50 | 71k | 87 |
| 11 | Gemini 3.7 Flash [high] | 65% | $2.18 | 107k | 125 |
| 12 | GLM 5.3 Flash [max] | 63% | $0.48 | 73k | 123 |
| 13 | DeepSeek V4-Pro [max] | 63% | $0.24 | 106k | 155 |
| 14 | Claude Opus 4.8 [max] | 59% | $13.22 | 135k | 120 |
| 15 | Qwen3.8-Max [xhigh] | 58% | $3.73 | 95k | 111 |
| 16 | Muse Spark 1.2 [xhigh] | 55% | $3.70 | 99k | 101 |
| 17 | Claude Sonnet 5 [max] | 54% | $26.40 | 214k | 268 |
| 18 | Grok 4.5 [high] | 54% | $2.42 | 36k | 61 |
| 19 | DeepSeek V4-Flash [max] | 53% | $0.10 | 108k | 153 |
| 20 | Muse Spark 1.1 [xhigh] | 53% | $2.36 | 74k | 96 |
| 21 | GPT-5.4 [xhigh] | 52% | $5.65 | 71k | 70 |
| 22 | Gemini 3.6 Flash [high] | 47% | $4.42 | 96k | 117 |
| 23 | GLM 5.2 [max] | 44% | $3.92 | 78k | 129 |
| 24 | Gemini 3.5 Flash [high] | 36% | $3.45 | 76k | 105 |
| 25 | Kimi K2.7 Code | 31% | $2.82 | 59k | 149 |
| 26 | Claude Sonnet 4.6 [high] | 30% | $5.52 | 76k | 134 |
| 27 | Gemini 3.1 Pro [high] | 12% | $2.14 | 28k | 76 |
DeepSWE “Best” picks the highest published reasoning effort per model (not the highest pass rate). Small gaps may not be statistically meaningful — confirm on deepswe.datacurve.ai.
When the cheaper one wins
Gemini 3.8 Flash is cheaper on output at $3.75 per million tokens against $10 for Gemini 2.5 Pro — about 2.7×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.
Run the model pickerEvidence confidence: High
How strong and complete the evidence behind this comparison is — not a prediction of which model is better.
- Pricing verified on both sides — Input and output rates are verified for both models.
- 4/5 core specs verified on both sides — Not published for at least one side: parameter count.
- 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
- Verified within the last 90 days — Newest catalog check was 8 days ago.
- Both models carry source citations — Each side has at least two catalog sources on record.
Source receipts
Each catalog figure was checked against the provider or an independent second source on the date shown.
- Gemini 2.5 Pro: Google — Gemini 2.5 Pro GA (accessed 2026-08-29)
- Gemini 2.5 Pro: Google AI pricing (accessed 2026-08-29)
- Gemini 3.8 Flash: Google — Gemini 3.8 Flash and 3.8 Flash Cyber (accessed 2026-09-03)
- Gemini 3.8 Flash: Gemini API pricing (gemini-3.8-flash $0.75/$3.75 intro) (accessed 2026-09-03)
- Gemini 3.8 Flash: DeepSWE 1.1 leaderboard — gemini-3.8-flash [high] 73.8% at $2.36/task (accessed 2026-09-03)
Related comparisons
- Claude Opus 5 vs Gemini 3.8 Flash
- Gemini 3.8 Flash vs GPT-5.6 Sol
- Amazon Nova 2 Pro vs Gemini 2.5 Pro
- Amazon Nova 2 Pro vs Gemini 3.8 Flash
- Claude Sonnet 5 vs Gemini 2.5 Pro
- Claude Sonnet 5 vs Gemini 3.8 Flash
Diving deeper on one model? Gemini 2.5 Pro · Gemini 3.8 Flash
Common questions
Gemini 2.5 Pro vs Gemini 3.8 Flash
Answered from the verified figures on this page rather than general guidance.
Is Gemini 2.5 Pro or Gemini 3.8 Flash cheaper for input?
Gemini 3.8 Flash is cheaper at $0.75 per million input tokens, against $1.25 for Gemini 2.5 Pro — roughly 1.7× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Gemini 2.5 Pro has tiered pricing: $1.25/$10 per MTok (≤200K); $2.50/$15 (>200K). Legacy but still widely listed. Gemini 3.8 Flash has tiered pricing: Intro $0.75/$3.75 per MTok through 2026-12-31, rising to $1.50/$7.50 from 2027-01-01; batch/Flex half price. Free tier available. Companion Gemini 3.8 Flash Cyber (defensive security) is restricted to the Fairwind Program with no public pricing.
Is Gemini 2.5 Pro or Gemini 3.8 Flash cheaper for output?
Gemini 3.8 Flash is cheaper at $3.75 per million output tokens, against $10 for Gemini 2.5 Pro — roughly 2.7× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Gemini 2.5 Pro has tiered pricing: $1.25/$10 per MTok (≤200K); $2.50/$15 (>200K). Legacy but still widely listed. Gemini 3.8 Flash has tiered pricing: Intro $0.75/$3.75 per MTok through 2026-12-31, rising to $1.50/$7.50 from 2027-01-01; batch/Flex half price. Free tier available. Companion Gemini 3.8 Flash Cyber (defensive security) is restricted to the Fairwind Program with no public pricing.
Which has the larger context window, Gemini 2.5 Pro or Gemini 3.8 Flash?
Both accept about 1.05M tokens of context, so document length will not decide between them.
Do Gemini 2.5 Pro and Gemini 3.8 Flash support the same reasoning levels?
Yes — both accept the same effort settings: "low", "medium", "high". Higher effort costs more and takes longer, so start low and raise it only where output quality actually improves.
Should I use Gemini 2.5 Pro or Gemini 3.8 Flash?
Both sit in the balanced tier, so the choice usually comes down to price and context rather than capability. Gemini 2.5 Pro suits long documents; Gemini 3.8 Flash suits agentic coding at scale.
Next step
Choosing between them
The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.
- Input price: Gemini 3.8 Flash costs $0.75 per 1M tokens versus $1.25 for Gemini 2.5 Pro — a 1.7x difference at the headline tier.
- Measured capability: Gemini 3.8 Flash leads Artificial Analysis Intelligence Index 58.7 to 47 (measured 2026-08-14).
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.