Model comparison
Gemini 3.7 Flash vs Gemini 3.8 Flash
Two Google tiers compared on the figures that decide which one a workload actually needs.
Catalog record checked September 5, 2026Individual provider fields may changeEvidence confidence: High — see receipts below
Gemini 3.7 Flash
Budget
Gemini 3.8 Flash
Balanced
| Specification | Gemini 3.7 Flash | Gemini 3.8 Flash |
|---|---|---|
| Provider | ||
| Tier | Budget | Balanced |
| Context window | 1.05M | 1.05M |
| Max output | 66K | 66K |
| Input / 1M tokens | $0.75 | $0.75 |
| Output / 1M tokens | $3.75 | $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-3.7-flash | gemini-3.8-flash |
| Released | August 13, 2026 | September 2, 2026 |
| Artificial Analysis Intelligence Index [high] (2026-08-14) | 56 | Winner: 58.7 |
| Terminal-Bench 2.1 (2026-08) | 85.8 | Winner: 89.4 |
| DeepSWE 1.1 (2026-08) | 65.3 | Not verifiedUnverified |
| Humanity's Last Exam (2026-08) | 53.6 | Winner: 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).
- 2026-08: Google DeepMind model evaluation report (vendor, HLE-Verified full set)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.
Pricing tiers: Gemini 3.7 Flash: Intro price $0.75/$3.75 per MTok through 2026-12-31, rising to $1.50/$7.50 from 2027-01-01. Multimodal input. · 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 3.7 Flash
Gemini 3.7 Flash is Google's efficiency-first multimodal Flash (3.8 Flash of 2026-09-02 is newer and stronger; Google keeps 3.7 for cost-focused routes).
Best for
- High-volume multimodal
- Agent loops
- Cost-sensitive work
Watch out
Intro pricing doubles on 2027-01-01; lock rates if deploying long-term.
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
Both charge $3.75 per million output tokens at standard rates, so output price is not the split. Prefer the row whose “best for” line matches the job, then confirm the live vendor rate.
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.
- 3 shared named benchmarks with differing scores — Measured on: Artificial Analysis Intelligence Index, Terminal-Bench 2.1, Humanity's Last Exam.
- Verified within the last 90 days — Newest catalog check was 6 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 3.7 Flash: Google — Gemini 3.7 Flash (accessed 2026-08-29)
- Gemini 3.7 Flash: Google Cloud Gemini 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 3.7 Flash
- Claude Opus 5 vs Gemini 3.8 Flash
- Gemini 3.7 Flash vs GLM 5.3 Flash
- Gemini 3.7 Flash vs GPT-5.6 Luna
- Gemini 3.7 Flash vs GPT-5.6 Sol
- Gemini 3.7 Flash vs Grok 4.6
Diving deeper on one model? Gemini 3.7 Flash · Gemini 3.8 Flash
Common questions
Gemini 3.7 Flash vs Gemini 3.8 Flash
Answered from the verified figures on this page rather than general guidance.
Is Gemini 3.7 Flash or Gemini 3.8 Flash cheaper for input?
Both cost $0.75 per million input tokens at standard rates, so input price is not a deciding factor between them.
Is Gemini 3.7 Flash or Gemini 3.8 Flash cheaper for output?
Both cost $3.75 per million output tokens at standard rates, so output price is not a deciding factor between them.
Which has the larger context window, Gemini 3.7 Flash or Gemini 3.8 Flash?
Both accept about 1.05M tokens of context, so document length will not decide between them.
Do Gemini 3.7 Flash 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 3.7 Flash or Gemini 3.8 Flash?
Gemini 3.7 Flash is the budget tier and Gemini 3.8 Flash the balanced tier. The useful question is whether your hardest task actually fails on the cheaper one — most production volume such as classification, extraction and summarisation does not.
Next step
Choosing between them
The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.
- Measured capability: Gemini 3.8 Flash leads Artificial Analysis Intelligence Index 58.7 to 56 (measured 2026-08-14).
- Positioning: Gemini 3.7 Flash sits in the budget tier, Gemini 3.8 Flash in the balanced tier — most production volume (classification, extraction, summarisation) does not need the pricier tier.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.