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Comparison · 3 models · Updated Nov 2, 2026

Mercury 2 vs Grok 4.20 (Non-Reasoning) vs Qwen3.5 9B Base

Too close to call on our weighted score (Grok 4.20 (Non-Reasoning) 52, Mercury 2 52, Qwen3.5 9B Base 50). The right pick depends on what you value most.

  1. Inception

    Mercury 2

    Released Feb 24, 2026

    52/100
    • ECI—
    • Price$0.25 / $0.75
    • Context128K
  2. xAI

    Grok 4.20 (Non-Reasoning)

    Released Mar 9, 2026

    52/100
    • ECI—
    • Price$1.25 / $2.50
    • Context1M
  3. Alibaba (Qwen)

    Qwen3.5 9B Base

    Released Feb 26, 2026

    50/100
    • ECI—
    • Price$0.30 / $0.807
    • Context262K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Grok 4.20 (Non-Reasoning) 52/100, Mercury 2 52/100, Qwen3.5 9B Base 50/100), so choose by what matters most for your work: Mercury 2 on price and Grok 4.20 (Non-Reasoning) for long inputs. 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 priceMercury 2Mercury 2 $0.375 · Qwen3.5 9B Base $0.427 · Grok 4.20 (Non-Reasoning) $1.56 per 1M tokens (3:1 blend)
  • Longest contextGrok 4.20 (Non-Reasoning)Grok 4.20 (Non-Reasoning) 1,000,000 · Qwen3.5 9B Base 262,144 · Mercury 2 128,000 tokens
  • Widest inputsGrok 4.20 (Non-Reasoning) and Qwen3.5 9B BaseMercury 2: Text · Grok 4.20 (Non-Reasoning): Text, Images, PDFs · Qwen3.5 9B Base: Text, Images, Video
  • Self-hostingQwen3.5 9B BasePublishes downloadable weights (Apache-2.0)
How the score is built
MeasureWeightMercury 2Grok 4.20 (Non-Reasoning)Qwen3.5 9B Base
Price50%673965
Inputs & features30%457035
Context window20%246037
Overall100%52/10052/10050/100

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.

Mercury 2 vs Grok 4.20 (Non-Reasoning) vs Qwen3.5 9B Base specifications side by side
SpecificationMercury 2InceptionGrok 4.20 (Non-Reasoning)xAIQwen3.5 9B BaseAlibaba (Qwen)
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.25 (best)$1.25$0.30
Output$0.75 (best)$2.50$0.807
Cached input$0.025 (best)$0.20—
Blended (3:1)$0.375 (best)$1.56$0.427
Long-context rateSame rateOver 200K: $2.50 / $5.00Same rate
Price sourceOfficial Inception APIOfficial xAI APIMedian of 1 providers
Limits
Context window128,000 tokens1,000,000 tokens (best)262,144 tokens
Max output50,000 tokens30,000 tokens65,536 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoYesNo
AudioNoNoNo
VideoNoNoYes
ReasoningYeslow · medium · highNoNo
Tool callingYesYesNo
Structured outputYesYesNo
Availability
WeightsProprietaryProprietaryOpenApache-2.0
API model IDmercury-2grok-4.20-0309-non-reasoning—
API providers713 (best)1
ReleasedFeb 24, 2026Mar 9, 2026Feb 26, 2026
Knowledge cutoff———
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.

  • Mercury 2$4.00
  • Grok 4.20 (Non-Reasoning)$17.50
  • Qwen3.5 9B Base$4.61
04 — Questions

Which should you choose?

Which is better: Mercury 2, Grok 4.20 (Non-Reasoning) or Qwen3.5 9B Base?

It is close. Our weighted score puts them within a point (Grok 4.20 (Non-Reasoning) 52/100, Mercury 2 52/100, Qwen3.5 9B Base 50/100), so choose by what matters most for your work: Mercury 2 on price and Grok 4.20 (Non-Reasoning) for long inputs. 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, Mercury 2, Grok 4.20 (Non-Reasoning) or Qwen3.5 9B Base?

Mercury 2 is cheaper at $0.25 input / $0.75 output per million tokens (official Inception API price). Qwen3.5 9B Base costs $0.30 input / $0.807 output per million tokens (median across 1 API provider); Grok 4.20 (Non-Reasoning) costs $1.25 input / $2.50 output per million tokens (official xAI API price). At a typical mix of three input tokens to one output token, that is $0.375 per million tokens for Mercury 2 versus $0.427 for Qwen3.5 9B Base (1.1× as much) and $1.56 for Grok 4.20 (Non-Reasoning) (4.2× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Mercury 2 has not been scored yet, Grok 4.20 (Non-Reasoning) has not been scored yet and Qwen3.5 9B Base has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Mercury 2, Grok 4.20 (Non-Reasoning) and Qwen3.5 9B Base yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen3.5 9B Base does not support tool calling, which most coding agents need.

Which has the bigger context window?

Grok 4.20 (Non-Reasoning) has the largest context window at 1,000,000 tokens, against 262,144 for Qwen3.5 9B Base and 128,000 for Mercury 2. Maximum output per response: Mercury 2 up to 50,000, Grok 4.20 (Non-Reasoning) up to 30,000, Qwen3.5 9B Base up to 65,536 tokens.

Which can read images, PDFs, audio or video?

Mercury 2 accepts text; Grok 4.20 (Non-Reasoning) accepts text, images and PDFs; Qwen3.5 9B Base accepts text, images and video. Grok 4.20 (Non-Reasoning) handles the widest range of inputs.

Are any of these open source?

Qwen3.5 9B Base publishes its weights (Apache-2.0) and can be self-hosted; Mercury 2 and Grok 4.20 (Non-Reasoning) is proprietary.

Which is newer?

Grok 4.20 (Non-Reasoning) is the newest, released Mar 9, 2026. Qwen3.5 9B Base came out Feb 26, 2026; Mercury 2 came out Feb 24, 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.