Nemotron 3 Ultra 550B A55B vs Kimi K2 Thinking vs Qwen3.6 27B
Qwen3.6 27B comes out ahead, 65 to 62 and 58 on our weighted score, though Nemotron 3 Ultra 550B A55B is 26% cheaper per token.
NVIDIA
Nemotron 3 Ultra 550B A55B
62/100- ECI146.2
- Price$0.50 / $2.50
- Context1M
Moonshot AI
Kimi K2 Thinking
58/100- ECI146.0
- Price$0.60 / $2.50
- Context262K
- Our pick
Alibaba (Qwen)
Qwen3.6 27B
65/100- ECI146.5
- Price$0.60 / $3.60
- Context262K
Qwen3.6 27B is our pick
Qwen3.6 27B is the better all-round choice, scoring 65/100 against Nemotron 3 Ultra 550B A55B (62) and Kimi K2 Thinking (58). It leads on inputs & features. Nemotron 3 Ultra 550B A55B wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3.6 27BCapabilities Index (ECI): Qwen3.6 27B 146.5 · Nemotron 3 Ultra 550B A55B 146.2 · Kimi K2 Thinking 146.0
- Lowest priceNemotron 3 Ultra 550B A55BNemotron 3 Ultra 550B A55B $1.00 · Kimi K2 Thinking $1.07 · Qwen3.6 27B $1.35 per 1M tokens (3:1 blend)
- Longest contextNemotron 3 Ultra 550B A55BNemotron 3 Ultra 550B A55B 1,000,000 · Kimi K2 Thinking 262,144 · Qwen3.6 27B 262,144 tokens
- Widest inputsQwen3.6 27BNemotron 3 Ultra 550B A55B: Text · Kimi K2 Thinking: Text · Qwen3.6 27B: Text, Images, Audio, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Nemotron 3 Ultra 550B A55B | Kimi K2 Thinking | Qwen3.6 27B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 73 | 73 | 74 |
| Price | 25% | 50 | 48 | 44 |
| Inputs & features | 15% | 45 | 35 | 90 |
| Context window | 10% | 60 | 37 | 37 |
| Overall | 100% | 62/100 | 58/100 | 65/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 146.2 | 146.0 | 146.5 (best) |
| ECI rank | #70 of 148 | #72 of 148 | #68 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 85.4% | 84.2% | 85.9% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 35.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 86.7% | 83.1% | 91.1% (best) |
| Price per million tokens | |||
| Input | $0.50 (best) | $0.60 | $0.60 |
| Output | $2.50 (best) | $2.50 (best) | $3.60 |
| Cached input | $0.15 | — | — |
| Blended (3:1) | $1.00 (best) | $1.07 | $1.35 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Nvidia API | Median of 10 providers | Official Alibaba API |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 262,144 tokens | 262,144 tokens |
| Max output | 128,000 tokens | 262,144 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | nvidia/nemotron-3-ultra-550b-a55b | — | qwen3.6-27b |
| API providers | 21 | 10 | 27 (best) |
| Released | Jun 4, 2026 | Nov 6, 2025 | Apr 22, 2026 |
| Knowledge cutoff | — | Aug 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Nemotron 3 Ultra 550B A55B$10.00
Kimi K2 Thinking$11.00
Qwen3.6 27B$13.20
Which should you choose?
Which is better: Nemotron 3 Ultra 550B A55B, Kimi K2 Thinking or Qwen3.6 27B?
Qwen3.6 27B is the better all-round choice, scoring 65/100 against Nemotron 3 Ultra 550B A55B (62) and Kimi K2 Thinking (58). It leads on inputs & features. Nemotron 3 Ultra 550B A55B wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Nemotron 3 Ultra 550B A55B, Kimi K2 Thinking or Qwen3.6 27B?
Nemotron 3 Ultra 550B A55B is cheaper at $0.50 input / $2.50 output per million tokens (official Nvidia API price). Kimi K2 Thinking costs $0.60 input / $2.50 output per million tokens (median across 10 API providers); Qwen3.6 27B costs $0.60 input / $3.60 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $1.00 per million tokens for Nemotron 3 Ultra 550B A55B versus $1.07 for Kimi K2 Thinking (1.1× as much) and $1.35 for Qwen3.6 27B (1.4× as much).
Which scores higher on benchmarks?
Qwen3.6 27B scores higher on the Capabilities Index (ECI): Qwen3.6 27B 146.5 (#68 of 148), Nemotron 3 Ultra 550B A55B 146.2 (#70 of 148) and Kimi K2 Thinking 146.0 (#72 of 148). The confidence ranges of the top two overlap (144.2–147.9 vs 143.9–148.1), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.6 27B 85.9%, Nemotron 3 Ultra 550B A55B 85.4%, Kimi K2 Thinking 84.2%; OTIS Mock AIME 2024–2025 — Qwen3.6 27B 91.1%, Nemotron 3 Ultra 550B A55B 86.7%, Kimi K2 Thinking 83.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Nemotron 3 Ultra 550B A55B, Kimi K2 Thinking and Qwen3.6 27B yet, so there is no like-for-like coding score. On overall capability, Qwen3.6 27B 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?
Nemotron 3 Ultra 550B A55B has the largest context window at 1,000,000 tokens, against 262,144 for Kimi K2 Thinking and 262,144 for Qwen3.6 27B. Maximum output per response: Nemotron 3 Ultra 550B A55B up to 128,000, Kimi K2 Thinking up to 262,144, Qwen3.6 27B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Nemotron 3 Ultra 550B A55B accepts text; Kimi K2 Thinking accepts text; Qwen3.6 27B accepts text, images, audio and video. Qwen3.6 27B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Nemotron 3 Ultra 550B A55B is the newest, released Jun 4, 2026. Qwen3.6 27B came out Apr 22, 2026; Kimi K2 Thinking came out Nov 6, 2025. Knowledge cutoff: Kimi K2 Thinking Aug 2024.
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 Oct 4, 2026.