Model comparison
Grok 4.1 Fast vs Llama 3.1-8B
Grok 4.1 Fast is the stronger model overall, scoring 41.4 to 23.0 on the Noometry Index. Llama 3.1-8B costs 4.8× less per token, which makes it the better buy when Grok 4.1 Fast's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. Grok 4.1 Fast scores higher in 9 categories and Llama 3.1-8B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.1 Fast leads 43.4 to 14.9.
- The biggest single-benchmark swing is Berkeley Function Calling Leaderboard: 69.6% for Grok 4.1 Fast and 25.8% for Llama 3.1-8B.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 per million input/output tokens, against $0.20 / $0.50 for Grok 4.1 Fast.
- Llama 3.1-8B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.1 Fast | Llama 3.1-8B | |
|---|---|---|
| Provider | xAI | Meta |
| Noometry Index | 41.4 | 23.0 |
| Released | 2025-06-27 | 2024-07-23 |
| Weights | Proprietary | Open |
| Context window | 128K | 128K |
| Max output | 30K | 4K |
| Input $ / M tokens | $0.20 | $0.05 |
| Output $ / M tokens | $0.50 | $0.08 |
| Results tracked | 32 | 43 |
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Category by category
Coding Grok 4.1 Fast leads
Grok 4.1 Fast: 34.1 (#245), Llama 3.1-8B: 20.2 (#340)
| Benchmark | Grok 4.1 Fast | Llama 3.1-8B |
|---|---|---|
| LMArena Coding | 1411 | 1195 |
| LMArena WebDev | 1242 | — |
| SciCode | — | 13.2% |
| WeirdML | — | 1.7% |
| BigCodeBench Instruct | — | 32.8% |
| BigCodeBench Complete | — | 40.5% |
| ALE-Bench | 394.93 | — |
| HumanEval+ | — | 62.8% |
| MBPP+ | — | 55.6% |
Agentic & Tool Use Grok 4.1 Fast leads
Grok 4.1 Fast: 36.3 (#39), Llama 3.1-8B: 22.5 (#131)
| Benchmark | Grok 4.1 Fast | Llama 3.1-8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 69.6% | 25.8% |
| τ²-bench Banking | 13.1% | — |
| BALROG | — | 15.1% |
| LMArena Search | 1171 | — |
| Vending-Bench 2 | 1,107 | — |
Reasoning Grok 4.1 Fast leads
Grok 4.1 Fast: 43.4 (#49), Llama 3.1-8B: 14.9 (#321)
| Benchmark | Grok 4.1 Fast | Llama 3.1-8B |
|---|---|---|
| LMArena Hard Prompts | 1407 | 1175 |
| DTBench | 87.7% | 50.9% |
| SimpleBench | 56% | — |
| NYT Connections (extended) | 87.4% | — |
| CritPt | — | 0% |
| Chess Puzzles | — | 0% |
| LMCA | — | 5.4% |
| Epoch Capabilities Index | — | 116.57 |
| ForecastBench | 61 | — |
| PIQA | — | 81.2% |
Math Grok 4.1 Fast leads
Grok 4.1 Fast: 31.9 (#221), Llama 3.1-8B: 10.2 (#317)
| Benchmark | Grok 4.1 Fast | Llama 3.1-8B |
|---|---|---|
| LMArena Math | 1408 | 1179 |
| MathArena Final-Answer Competitions | 60.9% | — |
| OTIS Mock AIME 2024-2025 | — | 1.7% |
| ProofBench | 4% | — |
| Omni-MATH | — | 13.7% |
| MATH Level 5 | — | 22.9% |
| GSM8K | — | 82.4% |
Knowledge Grok 4.1 Fast leads
Grok 4.1 Fast: 33.1 (#207), Llama 3.1-8B: 8.0 (#307)
| Benchmark | Grok 4.1 Fast | Llama 3.1-8B |
|---|---|---|
| LMArena Expert | 1399 | 1144 |
| GPQA Diamond | — | 27% |
| MMLU-Pro | — | 40.6% |
| Vectara Hallucination Rate | 17.8% | — |
| GPQA (HELM) | — | 24.7% |
| BoolQ | — | 82.8% |
| MMLU | — | 56.1% |
Multimodal Not comparable
Grok 4.1 Fast: 37.0 (#76), Llama 3.1-8B: —
| Benchmark | Grok 4.1 Fast | Llama 3.1-8B |
|---|---|---|
| LMArena Vision | 1201 | — |
Multilingual Grok 4.1 Fast leads
Grok 4.1 Fast: 51.0 (#114), Llama 3.1-8B: 34.0 (#249)
| Benchmark | Grok 4.1 Fast | Llama 3.1-8B |
|---|---|---|
| LMArena Non-English | 1391 | 1148 |
| LMArena Chinese | 1441 | 1151 |
| LMArena French | 1415 | 1177 |
| LMArena German | 1404 | 1144 |
| LMArena Japanese | 1349 | 1061 |
| LMArena Korean | 1361 | 1053 |
| LMArena Russian | 1387 | 1158 |
| LMArena Spanish | 1413 | 1169 |
Instruction Following Grok 4.1 Fast leads
Grok 4.1 Fast: 72.7 (#133), Llama 3.1-8B: 58.9 (#258)
| Benchmark | Grok 4.1 Fast | Llama 3.1-8B |
|---|---|---|
| LMArena Instruction Following | 1376 | 1159 |
| IFEval | — | 74.3% |
Long Context Grok 4.1 Fast leads
Grok 4.1 Fast: 42.4 (#126), Llama 3.1-8B: 35.8 (#238)
| Benchmark | Grok 4.1 Fast | Llama 3.1-8B |
|---|---|---|
| LMArena Longer Query | 1390 | 1182 |
Writing & Preference Grok 4.1 Fast leads
Grok 4.1 Fast: 57.2 (#131), Llama 3.1-8B: 29.7 (#290)
| Benchmark | Grok 4.1 Fast | Llama 3.1-8B |
|---|---|---|
| LMArena Text | 1408 | 1187 |
| LMArena Creative Writing | 1394 | 1154 |
| EQ-Bench Creative Writing | 1327 | 713 |
| LMArena Multi-Turn | 1389 | 1172 |
| WildBench | — | 68.7% |
Frequently asked questions
Is Grok 4.1 Fast better than Llama 3.1-8B?
Grok 4.1 Fast is the stronger model overall, scoring 41.4 to 23.0 on the Noometry Index. Llama 3.1-8B costs 4.8× less per token, which makes it the better buy when Grok 4.1 Fast's lead doesn't matter for your workload.
Which is cheaper, Grok 4.1 Fast or Llama 3.1-8B?
Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; Grok 4.1 Fast lists at $0.20 and $0.50.
Is Grok 4.1 Fast or Llama 3.1-8B better for coding?
Grok 4.1 Fast scores higher on coding benchmarks: 34.1 versus 20.2 in the Noometry coding category.
Which has the bigger context window?
Both accept 128K tokens.
How many benchmarks do Grok 4.1 Fast and Llama 3.1-8B share?
20 benchmarks have published results for both models. Grok 4.1 Fast has 32 scored results on Noometry and Llama 3.1-8B has 43.