Model comparison
Gemini 3.6 Flash vs Kimi K2.6
Google against Moonshot AI, compared on context, price, and verified benchmark results.
Catalog record checked August 14, 2026; individual provider fields may change.
Gemini 3.6 Flash
Budget
Moonshot AI
Kimi K2.6
Budget · Open weights
| Specification | Gemini 3.6 Flash | Kimi K2.6 |
|---|---|---|
| Provider | Moonshot AI | |
| Tier | Budget | Budget |
| Context window | Winner: 1.05M | 262K |
| Max output | 66K | Not verified |
| Input / 1M tokens | Winner: $0.75 | $0.95 |
| Output / 1M tokens | Winner: $3.75 | $4 |
| Weights | Closed | Open |
| Parameters | Not disclosed | 1T total / 32B active (MoE) |
| Reasoning levels | minimal, low, medium, high | Not verified |
| Modalities | text, image, video, audio, pdf | text, image, video |
| Released | July 21, 2026 | April 21, 2026 |
| Artificial Analysis Intelligence Index [high] (2026-08-08) | Winner: 52 | 45 |
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 3.6 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-3.6-flash`. Thinking levels are `minimal` / `low` / `medium` / `high` (API default medium). · Kimi K2.6: Cache-hit input is $0.16 / MTok; cache-miss input is $0.95 / MTok; output $4.00 / MTok (Moonshot list).
Gemini 3.6 Flash
Google's July 2026 Flash tier for multimodal volume work; 3.7 Flash is the newer coding/agent workhorse at the same introductory rate.
Best for
- Multimodal pipelines
- High-volume processing
- Video and audio input
Watch out
Introductory $0.75 input is 3.75× Luna; the $1.50 rate returns on 2027-01-01. 66K max output (65,536 tokens) is roughly half Luna's. Prefer 3.7 Flash for new coding-agent work unless you are pinned to 3.6.
Kimi K2.6
Open-weight mixture-of-experts model priced well below the closed frontier tiers.
Best for
- Cost-sensitive volume
- Self-hosting
- Avoiding vendor lock-in
Watch out
262K context is among the smaller windows here — a real constraint on long-document work.
Benchmark
DeepSWE 1.1 in context
Only Gemini 3.6 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 3.6 Flash vs Kimi K2.6
Answered from the verified figures on this page rather than general guidance.
Is Gemini 3.6 Flash or Kimi K2.6 cheaper for input?
Gemini 3.6 Flash is cheaper at $0.75 per million input tokens, against $0.95 for Kimi K2.6 — roughly 1.3× 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 3.6 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-3.6-flash`. Thinking levels are `minimal` / `low` / `medium` / `high` (API default medium). Kimi K2.6 has tiered pricing: Cache-hit input is $0.16 / MTok; cache-miss input is $0.95 / MTok; output $4.00 / MTok (Moonshot list).
Is Gemini 3.6 Flash or Kimi K2.6 cheaper for output?
Gemini 3.6 Flash is cheaper at $3.75 per million output tokens, against $4 for Kimi K2.6 — roughly 1.1× 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 3.6 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-3.6-flash`. Thinking levels are `minimal` / `low` / `medium` / `high` (API default medium). Kimi K2.6 has tiered pricing: Cache-hit input is $0.16 / MTok; cache-miss input is $0.95 / MTok; output $4.00 / MTok (Moonshot list).
Which has the larger context window, Gemini 3.6 Flash or Kimi K2.6?
Gemini 3.6 Flash accepts 1.05M tokens against 262K for Kimi K2.6. This only matters if you routinely send very long documents or large codebases.
Should I use Gemini 3.6 Flash or Kimi K2.6?
Both sit in the budget tier, so the choice usually comes down to price and context rather than capability. Gemini 3.6 Flash suits multimodal pipelines; Kimi K2.6 suits cost-sensitive volume.
Can I self-host Gemini 3.6 Flash or Kimi K2.6?
Kimi K2.6 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. Gemini 3.6 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.