Kolibri 1 vs Nemotron 3.5 Super 120B A12B vs Qwen3.8 Flash Next
Qwen3.8 Flash Next comes out ahead, 65 to 60 and 59 on our weighted score.
Aleph AlphaKolibri 1
60/100- ECI—
- Price$0.164 / $0.574
- Context1.05M
NVIDIANemotron 3.5 Super 120B A12B
59/100- ECI—
- Price$0.20 / $0.50
- Context1.05M
- Our pick
Alibaba (Qwen)Qwen3.8 Flash Next
65/100- ECI—
- Price$0.20 / $0.50
- Context262K
Qwen3.8 Flash Next is our pick
Qwen3.8 Flash Next is the better all-round choice, scoring 65/100 against Kolibri 1 (60) and Nemotron 3.5 Super 120B A12B (59). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceKolibri 1Kolibri 1 $0.266 · Nemotron 3.5 Super 120B A12B $0.275 · Qwen3.8 Flash Next $0.275 per 1M tokens (3:1 blend)
- Longest contextKolibri 1 and Nemotron 3.5 Super 120B A12BKolibri 1 1,048,576 · Nemotron 3.5 Super 120B A12B 1,048,576 · Qwen3.8 Flash Next 262,144 tokens
- Widest inputsQwen3.8 Flash NextKolibri 1: Text · Nemotron 3.5 Super 120B A12B: Text · Qwen3.8 Flash Next: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Kolibri 1 | Nemotron 3.5 Super 120B A12B | Qwen3.8 Flash Next |
|---|---|---|---|---|
| Price | 50% | 74 | 73 | 73 |
| Inputs & features | 30% | 35 | 35 | 70 |
| Context window | 20% | 61 | 61 | 37 |
| Overall | 100% | 60/100 | 59/100 | 65/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Kolibri 1Aleph Alpha | Nemotron 3.5 Super 120B A12BNVIDIA | Qwen3.8 Flash NextAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.164 (best) | $0.20 | $0.20 |
| Output | $0.574 | $0.50 (best) | $0.50 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.266 (best) | $0.275 | $0.275 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 4 providers | Median of 1 providers | Median of 4 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 1,048,576 tokens (best) | 262,144 tokens |
| Max output | — | 131,072 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache-2.0 | Open | Openqwen-community-1.0 |
| API model ID | — | — | — |
| API providers | 4 | 1 | 5 (best) |
| Released | Oct 3, 2026 | Oct 15, 2026 | Aug 27, 2026 |
| Knowledge cutoff | Jun 18, 2026 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Kolibri 1$2.78
- Nemotron 3.5 Super 120B A12B$3.00
- Qwen3.8 Flash Next$3.00
Which should you choose?
Which is better: Kolibri 1, Nemotron 3.5 Super 120B A12B or Qwen3.8 Flash Next?
Qwen3.8 Flash Next is the better all-round choice, scoring 65/100 against Kolibri 1 (60) and Nemotron 3.5 Super 120B A12B (59). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Kolibri 1, Nemotron 3.5 Super 120B A12B or Qwen3.8 Flash Next?
Kolibri 1 is cheaper at $0.164 input / $0.574 output per million tokens (median across 4 API providers). Nemotron 3.5 Super 120B A12B costs $0.20 input / $0.50 output per million tokens (median across 1 API provider); Qwen3.8 Flash Next costs $0.20 input / $0.50 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $0.266 per million tokens for Kolibri 1 versus $0.275 for Nemotron 3.5 Super 120B A12B (1× as much) and $0.275 for Qwen3.8 Flash Next (1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Kolibri 1 has not been scored yet, Nemotron 3.5 Super 120B A12B has not been scored yet and Qwen3.8 Flash Next has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Kolibri 1, Nemotron 3.5 Super 120B A12B and Qwen3.8 Flash Next yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Kolibri 1 and Nemotron 3.5 Super 120B A12B have the largest context windows (1,048,576 and 1,048,576 tokens), against 262,144 for Qwen3.8 Flash Next. Maximum output per response: Nemotron 3.5 Super 120B A12B up to 131,072, Qwen3.8 Flash Next up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Kolibri 1 accepts text; Nemotron 3.5 Super 120B A12B accepts text; Qwen3.8 Flash Next accepts text, images and video. Qwen3.8 Flash Next handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache-2.0 and qwen-community-1.0), so you can self-host them.
Which is newer?
Nemotron 3.5 Super 120B A12B is the newest, released Oct 15, 2026. Kolibri 1 came out Oct 3, 2026; Qwen3.8 Flash Next came out Aug 27, 2026. Knowledge cutoff: Kolibri 1 Jun 18, 2026.
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.
