Grok 4.20 vs Qwen3.5-9B
Grok 4.20 leads Qwen3.5-9B on the Artificial Analysis Intelligence Index, 25.7 to 13.3, and Qwen3.5-9B costs 16.7x less per output token ($0.15 vs $2.50 per million). Updated October 21, 2026; 11 benchmarks have a result for both.
Grok 4.20 or Qwen3.5-9B: which to pick
Only Grok 4.20 has a coding score, 33.3 on the Vibe Coding Index; Qwen3.5-9B has none, so the two cannot be ranked on coding.
Pick Qwen3.5-9B for output tokens 16.7x cheaper ($0.15 vs $2.50 per million) and work measured by Long context reasoning (AA-LCR), where it leads.
- Shared results
- 11
- Grok 4.20 only
- 44
- Qwen3.5-9B only
- 4
- Like-for-like categories
- 5 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Grok 4.20 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Grok 4.20
Grok 4.20 leads, 25.7 against 13.3.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Grok 4.20 has a GPQA Diamond result, 88.6%.
Directional only
Math
AIME
No call
Only Grok 4.20 has a AIME result, 96.5%.
Directional only
Knowledge
MMLU Pro
No call
Only Grok 4.20 has a MMLU Pro result, 86.3%.
Directional only
Web design
Design Arena: websites
No call
Only Grok 4.20 has a Design Arena: websites result, 1229.
Directional only
Long documents
Listed context window
Grok 4.20
Grok 4.20 takes 2M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-9B
Grok 4.20 $0.0025, Qwen3.5-9B $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Grok 4.20 has the number, $0.72.
Directional only
At a glance
- Coding index
- Grok 4.20 33.3 from 2 benchmarks, Qwen3.5-9B not benchmarked.
- Widest category
- Coding, 30.9 points apart on average over 2 shared benchmarks.
- Widest single gap
- Terminal-Bench: Grok 4.20 57.3% against Qwen3.5-9B 9.2%, 48.1 points apart on a 0 to 100 scale.
- Output price
- Grok 4.20 $2.50 against Qwen3.5-9B $0.15 per million output tokens, 16.7x apart.
- Context window
- Grok 4.20 takes 2M tokens, Qwen3.5-9B 262K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Grok 4.20 | Bars | Qwen3.5-9B | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 3 | 1 | ||
| All shared boards | 10 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Grok 4.20 | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 23.5 | Only Qwen3.5-9B measured |
| LiveCodeBench (Vals AI) | 84.3% | Not measured | Only Grok 4.20 measured |
| SWE-bench Verified (Vals AI) | 72.2% | Not measured | Only Grok 4.20 measured |
| Vibe Code Bench (Vals AI) | 4.1% | Not measured | Only Grok 4.20 measured |
| Code migration (Vals AI) | 0.3% | Not measured | Only Grok 4.20 measured |
| Terminal-Bench 2.1 (Vals AI) | 44.2% | Not measured | Only Grok 4.20 measured |
| SciCode | Not measured | 29.5% | Only Qwen3.5-9B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.9% | 24.2% | Grok 4.20 |
| Terminal-Bench | 57.3% | 9.2% | Grok 4.20 |
| WeirdML | 52.3% | Not measured | Only Grok 4.20 measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Grok 4.20 | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Intelligence Index | 25.7 | 13.3 | Grok 4.20 |
| Epoch Capabilities Index | 152.1 | 139.3 | Grok 4.20 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Grok 4.20 | Qwen3.5-9B | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1144 | Not measured | Only Grok 4.20 measured |
| Design Arena: agents building full-stack apps | 1054 | Not measured | Only Grok 4.20 measured |
| Design Arena: agents building mobile apps | 1090 | Not measured | Only Grok 4.20 measured |
| Design Arena: agents building Android apps | 1052 | Not measured | Only Grok 4.20 measured |
| Design Arena: agents building Godot games | 1089 | Not measured | Only Grok 4.20 measured |
| Design Arena: HTML slides | 1180 | Not measured | Only Grok 4.20 measured |
| Finance Agent (Vals AI) | 28.5% | Not measured | Only Grok 4.20 measured |
| Tax Agent Bench (Vals AI) | 7.0% | Not measured | Only Grok 4.20 measured |
| Legal Research Bench (Vals AI) | 13.9% | Not measured | Only Grok 4.20 measured |
| Excel Modeling Benchmark (Vals AI) | 11.7% | Not measured | Only Grok 4.20 measured |
| τ²-Bench Telecom | 93.0% | 86.8% | Grok 4.20 |
| Vending-Bench 2 | $4,663 | Not measured | Only Grok 4.20 measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Grok 4.20 | Qwen3.5-9B | Leader |
|---|---|---|---|
| GPQA Diamond | 88.6% | Not measured | Only Grok 4.20 measured |
| MMMU Pro (Vals AI) | 83.5% | Not measured | Only Grok 4.20 measured |
| GPQA Diamond (Artificial Analysis run) | 91.1% | 80.6% | Grok 4.20 |
| Humanity's Last Exam (Artificial Analysis run) | 34.5% | 14.9% | Grok 4.20 |
| GPQA Diamond (Epoch AI run) | Not measured | 79.0% | Only Qwen3.5-9B measured |
| ARC-AGI | 89.5% | Not measured | Only Grok 4.20 measured |
| ARC-AGI-2 | 65.1% | Not measured | Only Grok 4.20 measured |
| Kagi LLM Benchmark | 75.0% | Not measured | Only Grok 4.20 measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Grok 4.20 | Qwen3.5-9B | Leader |
|---|---|---|---|
| AIME | 96.5% | Not measured | Only Grok 4.20 measured |
| OTIS Mock AIME | Not measured | 61.7% | Only Qwen3.5-9B measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Grok 4.20 | Qwen3.5-9B | Leader |
|---|---|---|---|
| MMLU Pro | 86.3% | Not measured | Only Grok 4.20 measured |
| LegalBench (Vals AI) | 77.7% | Not measured | Only Grok 4.20 measured |
| CaseLaw (Vals AI) | 54.4% | Not measured | Only Grok 4.20 measured |
| CorpFin (Vals AI) | 63.7% | Not measured | Only Grok 4.20 measured |
| TaxEval (Vals AI) | 74.1% | Not measured | Only Grok 4.20 measured |
| MortgageTax (Vals AI) | 45.4% | Not measured | Only Grok 4.20 measured |
| MedQA (Vals AI) | 94.5% | Not measured | Only Grok 4.20 measured |
| MedCode (Vals AI) | 32.2% | Not measured | Only Grok 4.20 measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Grok 4.20 | Qwen3.5-9B | Leader |
|---|---|---|---|
| Design Arena: websites | 1229 | Not measured | Only Grok 4.20 measured |
| Design Arena: UI components | 1199 | Not measured | Only Grok 4.20 measured |
| Design Arena: game dev | 1192 | Not measured | Only Grok 4.20 measured |
| Design Arena: data viz | 1217 | Not measured | Only Grok 4.20 measured |
| Design Arena: 3D | 1193 | Not measured | Only Grok 4.20 measured |
| Design Arena: all code categories | 1221 | Not measured | Only Grok 4.20 measured |
| Design Arena: SVG | 1164 | Not measured | Only Grok 4.20 measured |
| Design Arena: ASCII art | 1174 | Not measured | Only Grok 4.20 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | Grok 4.20 | Qwen3.5-9B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 38.2% | Not measured | Only Grok 4.20 measured |
| MedScribe (Vals AI) | 63.4% | Not measured | Only Grok 4.20 measured |
| Vals Multimodal Index | 39.1% | Not measured | Only Grok 4.20 measured |
| IFBench | 81.2% | 66.7% | Grok 4.20 |
| Long context reasoning (AA-LCR) | 69.0% | 70.0% | Qwen3.5-9B |
| DTBench | 90.1% | 71.2% | Grok 4.20 |
| LMCA | 38.7% | 24.5% | Grok 4.20 |
| CL-bench | 22.2% | Not measured | Only Grok 4.20 measured |
| CL-bench Life | 11.9% | Not measured | Only Grok 4.20 measured |
| Neither model has a result on the other 37 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Grok 4.20 | Qwen3.5-9B | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Qwen3.5-9B costs less
Repository review
50K input + 3K output tokens
Qwen3.5-9B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-9B costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | SpaceXAI Grok 4.20 | Qwen3.5-9B |
|---|---|---|
| Maker | xAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | March 31, 2026 | March 10, 2026 |
| Context window | 2M | 262K |
| Input $/Mtok | $1.25 | $0.10 |
| Output $/Mtok | $2.50 | $0.15 |
| Coding index | 33.3 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | $0.72 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Grok 4.20 better than Qwen3.5-9B for coding?
Only Grok 4.20 has a coding score, 33.3 on the Vibe Coding Index; Qwen3.5-9B has none, so the two cannot be ranked on coding. Pick Qwen3.5-9B for output tokens 16.7x cheaper ($0.15 vs $2.50 per million) and work measured by Long context reasoning (AA-LCR), where it leads.
Which is cheaper, Grok 4.20 or Qwen3.5-9B?
Grok 4.20 costs $1.25 per million input tokens and $2.50 per million output tokens; Qwen3.5-9B costs $0.10 and $0.15. Cost per solved task is known for Grok 4.20 only.
Which has the bigger context window, Grok 4.20 or Qwen3.5-9B?
Grok 4.20, with 2M tokens against 262K.
How many benchmarks is the Grok 4.20 vs Qwen3.5-9B comparison based on?
11 benchmarks have a result for both models as of October 21, 2026. Grok 4.20's coding index rests on 2 independent benchmarks and Qwen3.5-9B's on 0. Where only one model has a result, the page says so instead of naming a winner.