Gemini 2.5 Flash vs Kimi K2 Instruct vs Qwen3.6 Plus
Too close to call on our weighted score (Gemini 2.5 Flash 66, Qwen3.6 Plus 66, Kimi K2 Instruct 50). The right pick depends on what you value most.
Google
Gemini 2.5 Flash
66/100- ECI140.6
- Price$0.30 / $2.50
- Context1.05M
Moonshot AI
Kimi K2 Instruct
50/100- ECI139.9
- Price$0.57 / $2.30
- Context131K
Alibaba (Qwen)
Qwen3.6 Plus
66/100- ECI147.8
- Price$0.50 / $3.00
- Context1M
Too close to call
It is close. Our weighted score puts them within a point (Gemini 2.5 Flash 66/100, Qwen3.6 Plus 66/100, Kimi K2 Instruct 50/100), so choose by what matters most for your work: Qwen3.6 Plus for raw capability, Gemini 2.5 Flash on price and Gemini 2.5 Flash for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3.6 PlusCapabilities Index (ECI): Qwen3.6 Plus 147.8 · Gemini 2.5 Flash 140.6 · Kimi K2 Instruct 139.9
- Lowest priceGemini 2.5 FlashGemini 2.5 Flash $0.85 · Kimi K2 Instruct $1.00 · Qwen3.6 Plus $1.13 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 FlashGemini 2.5 Flash 1,048,576 · Qwen3.6 Plus 1,000,000 · Kimi K2 Instruct 131,072 tokens
- Widest inputsGemini 2.5 FlashGemini 2.5 Flash: Text, Images, PDFs, Audio, Video · Kimi K2 Instruct: Text · Qwen3.6 Plus: Text, Images, Video
- Self-hostingKimi K2 InstructPublishes downloadable weights (Modified MIT)
| Measure | Weight | Gemini 2.5 Flash | Kimi K2 Instruct | Qwen3.6 Plus |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 65 | 64 | 74 |
| Price | 25% | 51 | 48 | 45 |
| Inputs & features | 15% | 100 | 25 | 80 |
| Context window | 10% | 61 | 25 | 60 |
| Overall | 100% | 66/100 | 50/100 | 66/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 140.6 | 139.9 | 147.8 (best) |
| ECI rank | #110 of 165 | #112 of 165 | #69 of 165 (best) |
| GPQA DiamondGraduate-level science questions | — | — | 88.4% |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 38.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 93.3% |
| SWE-bench VerifiedFixing real GitHub issues | — | — | 57.9% |
| SimpleQA VerifiedShort factual questions | — | — | 44.1% |
| Price per million tokens | |||
| Input | $0.30 (best) | $0.57 | $0.50 |
| Output | $2.50 | $2.30 (best) | $3.00 |
| Cached input | $0.03 (best) | — | $0.05 |
| Blended (3:1) | $0.85 (best) | $1.00 | $1.13 |
| Long-context rate | Same rate | Same rate | Over 256K: $2.00 / $6.00 |
| Price source | Official Google API | Median of 11 providers | Official Alibaba API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 131,072 tokens | 1,000,000 tokens |
| Max output | 65,536 tokens (best) | 32,768 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | Yes |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | OpenModified MIT | Proprietary |
| API model ID | gemini-2.5-flash | — | qwen3.6-plus |
| API providers | 32 (best) | 11 | 22 |
| Released | Jun 17, 2025 | Jul 11, 2025 | Apr 2, 2026 |
| Knowledge cutoff | Jan 2025 | — | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Gemini 2.5 Flash$8.00
Kimi K2 Instruct$10.30
Qwen3.6 Plus$11.00
Which should you choose?
Which is better: Gemini 2.5 Flash, Kimi K2 Instruct or Qwen3.6 Plus?
It is close. Our weighted score puts them within a point (Gemini 2.5 Flash 66/100, Qwen3.6 Plus 66/100, Kimi K2 Instruct 50/100), so choose by what matters most for your work: Qwen3.6 Plus for raw capability, Gemini 2.5 Flash on price and Gemini 2.5 Flash for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemini 2.5 Flash, Kimi K2 Instruct or Qwen3.6 Plus?
Gemini 2.5 Flash is cheaper at $0.30 input / $2.50 output per million tokens (official Google API price). Kimi K2 Instruct costs $0.57 input / $2.30 output per million tokens (median across 11 API providers); Qwen3.6 Plus costs $0.50 input / $3.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.85 per million tokens for Gemini 2.5 Flash versus $1.00 for Kimi K2 Instruct (1.2× as much) and $1.13 for Qwen3.6 Plus (1.3× as much).
Which scores higher on benchmarks?
Qwen3.6 Plus scores higher on the Capabilities Index (ECI): Qwen3.6 Plus 147.8 (#69 of 165), Gemini 2.5 Flash 140.6 (#110 of 165) and Kimi K2 Instruct 139.9 (#112 of 165). Their confidence ranges do not overlap (145.8–149.6 vs 138.4–142.1), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.5 Flash and Kimi K2 Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen3.6 Plus leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 2.5 Flash has the largest context window at 1,048,576 tokens, against 1,000,000 for Qwen3.6 Plus and 131,072 for Kimi K2 Instruct. Maximum output per response: Gemini 2.5 Flash up to 65,536, Kimi K2 Instruct up to 32,768, Qwen3.6 Plus up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Flash accepts text, images, PDFs, audio and video; Kimi K2 Instruct accepts text; Qwen3.6 Plus accepts text, images and video. Gemini 2.5 Flash handles the widest range of inputs.
Are any of these open source?
Kimi K2 Instruct publishes its weights (Modified MIT) and can be self-hosted; Gemini 2.5 Flash and Qwen3.6 Plus is proprietary.
Which is newer?
Qwen3.6 Plus is the newest, released Apr 2, 2026. Kimi K2 Instruct came out Jul 11, 2025; Gemini 2.5 Flash came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash Jan 2025, Qwen3.6 Plus Apr 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.