Model comparison
Grok 4.1 Fast vs Llama-3.3-70B-Instruct
Grok 4.1 Fast is the stronger model overall, scoring 40.9 to 30.3 on the Noometry Index. Llama-3.3-70B-Instruct costs 1.8× less per token, which makes it the better buy when Grok 4.1 Fast's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
MetaSummary
- They share 22 benchmarks with published results for both. Grok 4.1 Fast scores higher in 9 categories and Llama-3.3-70B-Instruct in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.1 Fast leads 42.3 to 13.7.
- The biggest single-benchmark swing is Berkeley Function Calling Leaderboard: 69.6% for Grok 4.1 Fast and 31.9% for Llama-3.3-70B-Instruct.
- Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $0.20 / $0.50 for Grok 4.1 Fast.
- Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.
Side by side
| Grok 4.1 Fast | Llama-3.3-70B-Instruct | |
|---|---|---|
| Provider | xAI | Meta |
| Noometry Index | 40.9 | 30.3 |
| Released | 2025-06-27 | 2024-12-06 |
| Weights | Proprietary | Open |
| Context window | 128K | 128K |
| Max output | 30K | 4K |
| Input $ / M tokens | $0.20 | $0.10 |
| Output $ / M tokens | $0.50 | $0.32 |
| Results tracked | 32 | 43 |
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Category by category
Coding Grok 4.1 Fast leads
Grok 4.1 Fast: 33.8 (#236), Llama-3.3-70B-Instruct: 30.6 (#284)
| Benchmark | Grok 4.1 Fast | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Coding | 1411 | 1268 |
| LMArena WebDev | 1241 | — |
| SciCode | — | 26% |
| WeirdML | — | 14.4% |
| BigCodeBench Instruct | — | 46.9% |
| LiveBench Coding | — | 36.6% |
| BigCodeBench Complete | — | 57.5% |
| ALE-Bench | 394.93 | — |
Agentic & Tool Use Grok 4.1 Fast leads
Grok 4.1 Fast: 36.1 (#35), Llama-3.3-70B-Instruct: 25.6 (#100)
| Benchmark | Grok 4.1 Fast | Llama-3.3-70B-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 69.6% | 31.9% |
| τ²-bench Banking | 13.1% | — |
| BALROG | — | 23% |
| LMArena Search | 1171 | — |
| Vending-Bench 2 | 1,107 | — |
Reasoning Grok 4.1 Fast leads
Grok 4.1 Fast: 42.3 (#45), Llama-3.3-70B-Instruct: 13.7 (#325)
| Benchmark | Grok 4.1 Fast | Llama-3.3-70B-Instruct |
|---|---|---|
| SimpleBench | 56% | 19.9% |
| LMArena Hard Prompts | 1407 | 1257 |
| DTBench | 87.7% | 59.5% |
| ForecastBench | 61 | 58.6 |
| NYT Connections (extended) | 87.4% | — |
| CritPt | — | 0% |
| LiveBench Reasoning | — | 50.8% |
| LiveBench Data Analysis | — | 49.5% |
| LMCA | — | 17.5% |
| Epoch Capabilities Index | — | 127.32 |
| LiveBench | — | 50.2% |
Math Grok 4.1 Fast leads
Grok 4.1 Fast: 30.9 (#201), Llama-3.3-70B-Instruct: 14.3 (#292)
| Benchmark | Grok 4.1 Fast | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Math | 1408 | 1268 |
| MathArena Final-Answer Competitions | 60.9% | — |
| OTIS Mock AIME 2024-2025 | — | 5.1% |
| ProofBench | 4% | — |
| LiveBench Math | — | 42.2% |
| MATH Level 5 | — | 41.6% |
Knowledge Grok 4.1 Fast leads
Grok 4.1 Fast: 32.6 (#203), Llama-3.3-70B-Instruct: 30.5 (#220)
| Benchmark | Grok 4.1 Fast | Llama-3.3-70B-Instruct |
|---|---|---|
| Vectara Hallucination Rate | 17.8% | 4.1% |
| LMArena Expert | 1398 | 1225 |
| GPQA Diamond | — | 47.4% |
| Confabulations | — | 22.8% |
| MMLU | — | 86.3% |
Multimodal Not comparable
Grok 4.1 Fast: 36.3 (#71), Llama-3.3-70B-Instruct: —
| Benchmark | Grok 4.1 Fast | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Vision | 1201 | — |
Multilingual Grok 4.1 Fast leads
Grok 4.1 Fast: 51.1 (#110), Llama-3.3-70B-Instruct: 40.1 (#215)
| Benchmark | Grok 4.1 Fast | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1391 | 1236 |
| LMArena Chinese | 1441 | 1217 |
| LMArena French | 1416 | 1280 |
| LMArena German | 1404 | 1251 |
| LMArena Japanese | 1347 | 1149 |
| LMArena Korean | 1361 | 1142 |
| LMArena Russian | 1387 | 1252 |
| LMArena Spanish | 1411 | 1269 |
Instruction Following Grok 4.1 Fast leads
Grok 4.1 Fast: 72.8 (#127), Llama-3.3-70B-Instruct: 71.3 (#152)
| Benchmark | Grok 4.1 Fast | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 1376 | 1242 |
| LiveBench Instruction Following | — | 82.7% |
Long Context Grok 4.1 Fast leads
Grok 4.1 Fast: 42.4 (#121), Llama-3.3-70B-Instruct: 26.4 (#290)
| Benchmark | Grok 4.1 Fast | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 1390 | 1256 |
| Fiction.LiveBench | — | 33.3% |
Writing & Preference Grok 4.1 Fast leads
Grok 4.1 Fast: 57.4 (#126), Llama-3.3-70B-Instruct: 47.8 (#203)
| Benchmark | Grok 4.1 Fast | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1408 | 1274 |
| LMArena Creative Writing | 1394 | 1250 |
| LMArena Multi-Turn | 1389 | 1279 |
| EQ-Bench Creative Writing | 1327 | — |
| LiveBench Language | — | 39.2% |
Frequently asked questions
Is Grok 4.1 Fast better than Llama-3.3-70B-Instruct?
Grok 4.1 Fast is the stronger model overall, scoring 40.9 to 30.3 on the Noometry Index. Llama-3.3-70B-Instruct costs 1.8× 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-3.3-70B-Instruct?
Llama-3.3-70B-Instruct is cheaper. It lists at $0.10 per million input tokens and $0.32 per million output tokens; Grok 4.1 Fast lists at $0.20 and $0.50.
Is Grok 4.1 Fast or Llama-3.3-70B-Instruct better for coding?
Grok 4.1 Fast scores higher on coding benchmarks: 33.8 versus 30.6 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-3.3-70B-Instruct share?
22 benchmarks have published results for both models. Grok 4.1 Fast has 32 scored results on Noometry and Llama-3.3-70B-Instruct has 43.