Model comparison
Gemini 3.7 Flash vs Ling 3.0 Flash
Google against InclusionAI, compared on context, price, and verified benchmark results.
Catalog record checked August 14, 2026; individual provider fields may change.
Gemini 3.7 Flash
Budget
InclusionAI
Ling 3.0 Flash
Budget · Open weights
| Specification | Gemini 3.7 Flash | Ling 3.0 Flash |
|---|---|---|
| Provider | InclusionAI | |
| Tier | Budget | Budget |
| Context window | Winner: 1.05M | 262K |
| Max output | 66K | Not verified |
| Input / 1M tokens | $0.75 | Winner: $0.075 |
| Output / 1M tokens | $3.75 | Winner: $0.22 |
| Weights | Closed | Open |
| Parameters | Not disclosed | 124B total / 5.1B active (MoE) |
| Reasoning levels | low, medium, high | Not verified |
| Modalities | text, image, video, audio, pdf | text |
| Released | August 13, 2026 | July 24, 2026 |
| Artificial Analysis Intelligence Index [high] (2026-08-14) | Winner: 56 | 38 |
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.
Pricing tiers: Gemini 3.7 Flash: Introductory paid-tier rates through 2026-12-31. From 2027-01-01 the standard paid rates are $1.50 / $7.50 per million tokens (Gemini API pricing). Cache is $0.075 / MTok through 2026-12-31, then $0.15. Wire calls to `gemini-3.7-flash`. Thinking levels are `low` / `medium` / `high` (API default medium; no MINIMAL).
Gemini 3.7 Flash
Google's 2026-08-13 Flash workhorse for coding and agents, three weeks after 3.6 Flash, at an introductory $0.75 / $3.75 per million tokens.
Best for
- Coding agents
- Multimodal agent loops
- High-volume Google API work
Watch out
Intro price doubles on 2027-01-01. DeepSWE 1.1 best-effort (high) is 65.3% at $2.18/task; medium scores 65.5% a few cents cheaper. 66K max output (65,536 tokens). Knowledge cutoff is March 2026 on some domains (January 2025 on others).
Ling 3.0 Flash
InclusionAI's cost-focused Flash tier for high-frequency hybrid reasoning and agent loops at low list rates.
Best for
- High-volume agent loops
- Cost-sensitive chat and extraction
- Fast hybrid reasoning
Watch out
Native context is 256Ki tokens (262,144). Confirm serving provider and current list before committing volume.
Benchmark
DeepSWE 1.1 in context
Only Gemini 3.7 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
Claude Opus 5 [max]
74%
Rows shown
24
Highest published reasoning effort per model (not best Pass@1)
Snapshot date
2026-08-13
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 | Claude Opus 5 [max] | 74% | $11.84 | 118k | 99 |
| 2 | GPT-5.6 Sol [max] | 73% | $8.39 | 60k | 61 |
| 3 | Claude Fable 5 [max] | 70% | $21.63 | 119k | 88 |
| 4 | GPT-5.6 Terra [max] | 70% | $4.95 | 72k | 76 |
| 5 | Kimi K3 [max] | 69% | $4.65 | 82k | 98 |
| 6 | GPT-5.6 Luna [max] | 67% | $3.03 | 73k | 102 |
| 7 | GPT-5.5 [xhigh] | 67% | $7.23 | 46k | 82 |
| 8 | Grok 4.6 [xhigh] | 67% | $5.50 | 71k | 87 |
| 9 | Gemini 3.7 Flash [high] | 65% | $2.18 | 107k | 125 |
| 10 | DeepSeek V4-Pro [max] | 63% | $0.24 | 106k | 155 |
| 11 | Claude Opus 4.8 [max] | 59% | $13.22 | 135k | 120 |
| 12 | Qwen3.8-Max [xhigh] | 58% | $3.73 | 95k | 111 |
| 13 | Muse Spark 1.2 [xhigh] | 55% | $3.70 | 99k | 101 |
| 14 | Claude Sonnet 5 [max] | 54% | $26.40 | 214k | 268 |
| 15 | Grok 4.5 [high] | 54% | $2.42 | 36k | 61 |
| 16 | DeepSeek V4-Flash [max] | 53% | $0.10 | 108k | 153 |
| 17 | Muse Spark 1.1 [xhigh] | 53% | $2.36 | 74k | 96 |
| 18 | GPT-5.4 [xhigh] | 52% | $5.65 | 71k | 70 |
| 19 | Gemini 3.6 Flash [high] | 47% | $4.42 | 96k | 117 |
| 20 | GLM 5.2 [max] | 44% | $3.92 | 78k | 129 |
| 21 | Gemini 3.5 Flash [high] | 36% | $3.45 | 76k | 105 |
| 22 | Kimi K2.7 Code | 31% | $2.82 | 59k | 149 |
| 23 | Claude Sonnet 4.6 [high] | 30% | $5.52 | 76k | 134 |
| 24 | 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.
Common questions
Gemini 3.7 Flash vs Ling 3.0 Flash
Answered from the verified figures on this page rather than general guidance.
Is Gemini 3.7 Flash or Ling 3.0 Flash cheaper for input?
Ling 3.0 Flash is cheaper at $0.075 per million input tokens, against $0.75 for Gemini 3.7 Flash — roughly 10× 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 3.7 Flash has tiered pricing: Introductory paid-tier rates through 2026-12-31. From 2027-01-01 the standard paid rates are $1.50 / $7.50 per million tokens (Gemini API pricing). Cache is $0.075 / MTok through 2026-12-31, then $0.15. Wire calls to `gemini-3.7-flash`. Thinking levels are `low` / `medium` / `high` (API default medium; no MINIMAL).
Is Gemini 3.7 Flash or Ling 3.0 Flash cheaper for output?
Ling 3.0 Flash is cheaper at $0.22 per million output tokens, against $3.75 for Gemini 3.7 Flash — roughly 17× 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 3.7 Flash has tiered pricing: Introductory paid-tier rates through 2026-12-31. From 2027-01-01 the standard paid rates are $1.50 / $7.50 per million tokens (Gemini API pricing). Cache is $0.075 / MTok through 2026-12-31, then $0.15. Wire calls to `gemini-3.7-flash`. Thinking levels are `low` / `medium` / `high` (API default medium; no MINIMAL).
Which has the larger context window, Gemini 3.7 Flash or Ling 3.0 Flash?
Gemini 3.7 Flash accepts 1.05M tokens against 262K for Ling 3.0 Flash. This only matters if you routinely send very long documents or large codebases.
Should I use Gemini 3.7 Flash or Ling 3.0 Flash?
Both sit in the budget tier, so the choice usually comes down to price and context rather than capability. Gemini 3.7 Flash suits coding agents; Ling 3.0 Flash suits high-volume agent loops.
Can I self-host Gemini 3.7 Flash or Ling 3.0 Flash?
Ling 3.0 Flash publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. Gemini 3.7 Flash is a closed model whose supported access paths are controlled by its provider.
Next step
Choosing between them
Tier and workload decide this more reliably than a leaderboard position does.
If both sit in the same tier, the decision usually comes down to context window and output price rather than headline capability — output tokens dominate real bills.
If one is a step up within the same provider, the useful question is whether your hardest task actually fails on the cheaper tier. Most production volume — classification, extraction, summarization — does not.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Muse Code, or Lovable? Compare agentic harnesses · Latest releases.