Grok 4.20 vs Llama 3.1 8B Instruct
Grok 4.20 leads Llama 3.1 8B Instruct on the Artificial Analysis Intelligence Index, 25.7 to 6.9, and Llama 3.1 8B Instruct costs 31.3x less per output token ($0.08 vs $2.50 per million). Updated October 21, 2026; 11 benchmarks have a result for both.
Grok 4.20 or Llama 3.1 8B Instruct: which to pick
Only Grok 4.20 has a coding score, 33.3 on the Vibe Coding Index; Llama 3.1 8B Instruct has none, so the two cannot be ranked on coding.
Pick Llama 3.1 8B Instruct for output tokens 31.3x cheaper ($0.08 vs $2.50 per million).
- Shared results
- 11
- Grok 4.20 only
- 44
- Llama 3.1 8B Instruct only
- 40
- 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 6.9.
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 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.1 8B Instruct
Grok 4.20 $0.0025, Llama 3.1 8B Instruct $0.0001 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, Llama 3.1 8B Instruct not benchmarked.
- Widest category
- Agentic work, 76.6 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Grok 4.20 93.0% against Llama 3.1 8B Instruct 16.4%, 76.6 points apart on a 0 to 100 scale.
- Output price
- Grok 4.20 $2.50 against Llama 3.1 8B Instruct $0.08 per million output tokens, 31.3x apart.
- Context window
- Grok 4.20 takes 2M tokens, Llama 3.1 8B Instruct 131K.
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 | Llama 3.1 8B Instruct | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 4 | 0 | ||
| All shared boards | 11 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Grok 4.20 | Llama 3.1 8B Instruct | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 5.4 | Only Llama 3.1 8B Instruct 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 |
| LiveCodeBench (Artificial Analysis run) | Not measured | 11.6% | Only Llama 3.1 8B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.9% | 0.8% | Grok 4.20 |
| Terminal-Bench | 57.3% | Not measured | Only Grok 4.20 measured |
| WeirdML | 52.3% | 1.7% | Grok 4.20 |
| LMArena Text: coding | Not measured | 1195 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: software and IT | Not measured | 1195 | Only Llama 3.1 8B Instruct measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Grok 4.20 | Llama 3.1 8B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 25.7 | 6.9 | Grok 4.20 |
| Epoch Capabilities Index | 152.1 | 116.5 | Grok 4.20 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Grok 4.20 | Llama 3.1 8B Instruct | 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% | 16.4% | Grok 4.20 |
| BALROG | Not measured | 15.1% | Only Llama 3.1 8B Instruct measured |
| Vending-Bench 2 | $4,663 | Not measured | Only Grok 4.20 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 25.8% | Only Llama 3.1 8B Instruct measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Grok 4.20 | Llama 3.1 8B Instruct | 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% | 25.9% | Grok 4.20 |
| Humanity's Last Exam (Artificial Analysis run) | 34.5% | 5.3% | Grok 4.20 |
| GPQA Diamond (Epoch AI run) | Not measured | 27.0% | Only Llama 3.1 8B Instruct measured |
| ARC-AGI | 89.5% | Not measured | Only Grok 4.20 measured |
| ARC-AGI-2 | 65.1% | Not measured | Only Grok 4.20 measured |
| LMArena Text: hard prompts | Not measured | 1175 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: expert | Not measured | 1144 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: hard prompts in English | Not measured | 1196 | Only Llama 3.1 8B Instruct measured |
| Kagi LLM Benchmark | 75.0% | Not measured | Only Grok 4.20 measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Grok 4.20 | Llama 3.1 8B Instruct | Leader |
|---|---|---|---|
| AIME | 96.5% | Not measured | Only Grok 4.20 measured |
| AA Math Index | Not measured | 4.3 | Only Llama 3.1 8B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 4.3% | Only Llama 3.1 8B Instruct measured |
| OTIS Mock AIME | Not measured | 1.7% | Only Llama 3.1 8B Instruct measured |
| MATH level 5 | Not measured | 22.9% | Only Llama 3.1 8B Instruct measured |
| GSM8K | Not measured | 82.4% | Only Llama 3.1 8B Instruct measured |
| LMArena Text: math | Not measured | 1179 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: mathematical work | Not measured | 1180 | Only Llama 3.1 8B Instruct measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | Grok 4.20 | Llama 3.1 8B Instruct | 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 |
| MMLU Pro (Artificial Analysis run) | Not measured | 47.6% | Only Llama 3.1 8B Instruct measured |
| MMLU | Not measured | 56.1% | Only Llama 3.1 8B Instruct measured |
| LMArena Text: science | Not measured | 1193 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: medicine and healthcare | Not measured | 1182 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: legal and government | Not measured | 1206 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: business and finance | Not measured | 1166 | Only Llama 3.1 8B Instruct measured |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Grok 4.20 | Llama 3.1 8B Instruct | 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 index40
| Benchmark | Grok 4.20 | Llama 3.1 8B Instruct | 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% | 28.6% | Grok 4.20 |
| Long context reasoning (AA-LCR) | 69.0% | 18.0% | Grok 4.20 |
| DTBench | 90.1% | 50.9% | Grok 4.20 |
| LMCA | 38.7% | 5.4% | Grok 4.20 |
| CL-bench | 22.2% | Not measured | Only Grok 4.20 measured |
| PIQA | Not measured | 81.2% | Only Llama 3.1 8B Instruct measured |
| CL-bench Life | 11.9% | Not measured | Only Grok 4.20 measured |
| LMArena Text | Not measured | 1187 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: instruction following | Not measured | 1159 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: creative writing | Not measured | 1154 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: English | Not measured | 1218 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: non-English | Not measured | 1148 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: Chinese | Not measured | 1151 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: German | Not measured | 1144 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: Japanese | Not measured | 1061 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: Korean | Not measured | 1053 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: French | Not measured | 1178 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: Spanish | Not measured | 1169 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: Russian | Not measured | 1158 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: multi-turn | Not measured | 1172 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: longer queries | Not measured | 1181 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: writing and language | Not measured | 1162 | Only Llama 3.1 8B Instruct measured |
| LMArena Text: entertainment and media | Not measured | 1145 | Only Llama 3.1 8B Instruct measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Grok 4.20 | Llama 3.1 8B Instruct | 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
Llama 3.1 8B Instruct costs less
Repository review
50K input + 3K output tokens
Llama 3.1 8B Instruct costs less
Agent loop
200K input + 10K output tokens
Llama 3.1 8B Instruct 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 | Meta Llama 3.1 8B Instruct |
|---|---|---|
| Maker | xAI | Meta Llama |
| Weights | No public weights listed | Open weights |
| Released | March 31, 2026 | July 23, 2024 |
| Context window | 2M | 131K |
| Input $/Mtok | $1.25 | $0.05 |
| Output $/Mtok | $2.50 | $0.08 |
| 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 Llama 3.1 8B Instruct for coding?
Only Grok 4.20 has a coding score, 33.3 on the Vibe Coding Index; Llama 3.1 8B Instruct has none, so the two cannot be ranked on coding. Pick Llama 3.1 8B Instruct for output tokens 31.3x cheaper ($0.08 vs $2.50 per million).
Which is cheaper, Grok 4.20 or Llama 3.1 8B Instruct?
Grok 4.20 costs $1.25 per million input tokens and $2.50 per million output tokens; Llama 3.1 8B Instruct costs $0.05 and $0.08. Cost per solved task is known for Grok 4.20 only.
Which has the bigger context window, Grok 4.20 or Llama 3.1 8B Instruct?
Grok 4.20, with 2M tokens against 131K.
How many benchmarks is the Grok 4.20 vs Llama 3.1 8B Instruct 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 Llama 3.1 8B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.