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Comparison · 3 models · Updated Oct 4, 2026

Nemotron 3 Super 120B A12B vs Qwen3.5 122B-A10B vs Mercury 2

Qwen3.5 122B-A10B comes out ahead, 58 to 54 and 53 on our weighted score, though Nemotron 3 Super 120B A12B is 3.1× cheaper per token.

  1. NVIDIA

    Nemotron 3 Super 120B A12B

    Released Mar 11, 2026

    54/100
    • ECI—
    • Price$0.20 / $0.80
    • Context262K
  2. Our pick

    Alibaba (Qwen)

    Qwen3.5 122B-A10B

    Released Feb 23, 2026

    58/100
    • ECI—
    • Price$0.40 / $3.20
    • Context262K
  3. Inception

    Mercury 2

    Released Feb 24, 2026

    53/100
    • ECI—
    • Price$0.25 / $0.75
    • Context128K
01 — Verdict

Qwen3.5 122B-A10B is our pick

Qwen3.5 122B-A10B is the better all-round choice, scoring 58/100 against Nemotron 3 Super 120B A12B (54) and Mercury 2 (53). 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 priceNemotron 3 Super 120B A12BNemotron 3 Super 120B A12B $0.35 · Mercury 2 $0.375 · Qwen3.5 122B-A10B $1.10 per 1M tokens (3:1 blend)
  • Longest contextNemotron 3 Super 120B A12B and Qwen3.5 122B-A10BNemotron 3 Super 120B A12B 262,144 · Qwen3.5 122B-A10B 262,144 · Mercury 2 128,000 tokens
  • Widest inputsQwen3.5 122B-A10BNemotron 3 Super 120B A12B: Text · Qwen3.5 122B-A10B: Text, Images, Audio, Video · Mercury 2: Text
  • Self-hostingNemotron 3 Super 120B A12B and Qwen3.5 122B-A10BPublishes downloadable weights
How the score is built
MeasureWeightNemotron 3 Super 120B A12BQwen3.5 122B-A10BMercury 2
Price50%724870
Inputs & features30%359045
Context window20%373724
Overall100%54/10058/10053/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Nemotron 3 Super 120B A12B vs Qwen3.5 122B-A10B vs Mercury 2 specifications side by side
SpecificationNemotron 3 Super 120B A12BNVIDIAQwen3.5 122B-A10BAlibaba (Qwen)Mercury 2Inception
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.20 (best)$0.40$0.25
Output$0.80$3.20$0.75 (best)
Cached input——$0.025
Blended (3:1)$0.35 (best)$1.10$0.375
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Nvidia APIOfficial Alibaba APIOfficial Inception API
Limits
Context window262,144 tokens (best)262,144 tokens (best)128,000 tokens
Max output262,144 tokens (best)65,536 tokens50,000 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoYesNo
VideoNoYesNo
ReasoningYesYesYeslow · medium · high
Tool callingYesYesYes
Structured outputNoYesYes
Availability
WeightsOpenOpenProprietary
API model IDnvidia/nemotron-3-super-120b-a12bqwen3.5-122b-a10bmercury-2
API providers19 (best)19 (best)1
ReleasedMar 11, 2026Feb 23, 2026Feb 24, 2026
Knowledge cutoff——Jan 1, 2025
03 — Cost

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 Super 120B A12B$3.60
  • Qwen3.5 122B-A10B$10.40
  • Mercury 2$4.00
04 — Questions

Which should you choose?

Which is better: Nemotron 3 Super 120B A12B, Qwen3.5 122B-A10B or Mercury 2?

Qwen3.5 122B-A10B is the better all-round choice, scoring 58/100 against Nemotron 3 Super 120B A12B (54) and Mercury 2 (53). 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, Nemotron 3 Super 120B A12B, Qwen3.5 122B-A10B or Mercury 2?

Nemotron 3 Super 120B A12B is cheaper at $0.20 input / $0.80 output per million tokens (official Nvidia API price). Mercury 2 costs $0.25 input / $0.75 output per million tokens (official Inception API price); Qwen3.5 122B-A10B costs $0.40 input / $3.20 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.35 per million tokens for Nemotron 3 Super 120B A12B versus $0.375 for Mercury 2 (1.1× as much) and $1.10 for Qwen3.5 122B-A10B (3.1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Nemotron 3 Super 120B A12B has not been scored yet, Qwen3.5 122B-A10B has not been scored yet and Mercury 2 has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Nemotron 3 Super 120B A12B, Qwen3.5 122B-A10B and Mercury 2 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?

Nemotron 3 Super 120B A12B and Qwen3.5 122B-A10B have the largest context windows (262,144 and 262,144 tokens), against 128,000 for Mercury 2. Maximum output per response: Nemotron 3 Super 120B A12B up to 262,144, Qwen3.5 122B-A10B up to 65,536, Mercury 2 up to 50,000 tokens.

Which can read images, PDFs, audio or video?

Nemotron 3 Super 120B A12B accepts text; Qwen3.5 122B-A10B accepts text, images, audio and video; Mercury 2 accepts text. Qwen3.5 122B-A10B handles the widest range of inputs.

Are any of these open source?

Nemotron 3 Super 120B A12B and Qwen3.5 122B-A10B publishes its weights and can be self-hosted; Mercury 2 is proprietary.

Which is newer?

Nemotron 3 Super 120B A12B is the newest, released Mar 11, 2026. Mercury 2 came out Feb 24, 2026; Qwen3.5 122B-A10B came out Feb 23, 2026. Knowledge cutoff: Mercury 2 Jan 1, 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 Oct 4, 2026.