Model comparison
Grok 4.20 Multi-Agent vs Mistral Small
Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 33.4 on the Noometry Index. Mistral Small costs 6.0× less per token, which makes it the better buy when Grok 4.20 Multi-Agent's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Mistral AISummary
- They share 18 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 9 categories and Mistral Small in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.20 Multi-Agent leads 43.9 to 19.8.
- Mistral Small is cheaper at $0.15 / $0.60 per million input/output tokens, against $1.25 / $2.50 for Grok 4.20 Multi-Agent.
- Grok 4.20 Multi-Agent accepts more context: 1M tokens versus 262K.
- Mistral Small has downloadable open weights; the other is API-only.
Side by side
| Grok 4.20 Multi-Agent | Mistral Small | |
|---|---|---|
| Provider | xAI | Mistral AI |
| Noometry Index | 46.2 | 33.4 |
| Released | 2026-03-09 | 2024-02-26 |
| Weights | Proprietary | Open |
| Context window | 1M | 262K |
| Max output | 30K | 256K |
| Input $ / M tokens | $1.25 | $0.15 |
| Output $ / M tokens | $2.50 | $0.60 |
| Results tracked | 20 | 39 |
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Category by category
Coding Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.0 (#92), Mistral Small: 34.0 (#247)
| Benchmark | Grok 4.20 Multi-Agent | Mistral Small |
|---|---|---|
| LMArena Coding | 1457 | 1362 |
| SciCode | — | 26.5% |
| BigCodeBench Instruct | — | 36.1% |
| LiveBench Coding | — | 36.2% |
| BigCodeBench Complete | — | 46.6% |
| ALE-Bench | — | 497.62 |
Agentic & Tool Use Not comparable
Grok 4.20 Multi-Agent: —, Mistral Small: 28.1 (#93)
| Benchmark | Grok 4.20 Multi-Agent | Mistral Small |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.1% |
| LMArena Search | 1204 | — |
Reasoning Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.9 (#48), Mistral Small: 19.8 (#250)
| Benchmark | Grok 4.20 Multi-Agent | Mistral Small |
|---|---|---|
| LMArena Hard Prompts | 1448 | 1335 |
| Kagi LLM Benchmark | — | 37.8% |
| NYT Connections (extended) | 89.6% | — |
| CritPt | — | 0% |
| LiveBench Reasoning | — | 44.8% |
| DTBench | — | 70.9% |
| LiveBench Data Analysis | — | 53.7% |
| LMCA | — | 20.6% |
| LiveBench | — | 44% |
Math Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 39.4 (#104), Mistral Small: 16.4 (#293)
| Benchmark | Grok 4.20 Multi-Agent | Mistral Small |
|---|---|---|
| LMArena Math | 1442 | 1341 |
| OTIS Mock AIME 2024-2025 | — | 5.8% |
| LiveBench Math | — | 39.9% |
| MATH Level 5 | — | 46.8% |
Knowledge Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 40.4 (#119), Mistral Small: 31.0 (#222)
| Benchmark | Grok 4.20 Multi-Agent | Mistral Small |
|---|---|---|
| LMArena Expert | 1445 | 1291 |
| GPQA Diamond | — | 47.5% |
| Vectara Hallucination Rate | — | 5.1% |
| MMLU | — | 68.7% |
Multimodal Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 40.5 (#48), Mistral Small: 33.5 (#96)
| Benchmark | Grok 4.20 Multi-Agent | Mistral Small |
|---|---|---|
| LMArena Vision | 1259 | 1142 |
Multilingual Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 54.4 (#43), Mistral Small: 45.5 (#169)
| Benchmark | Grok 4.20 Multi-Agent | Mistral Small |
|---|---|---|
| LMArena Non-English | 1440 | 1315 |
| LMArena Chinese | 1475 | 1340 |
| LMArena French | 1466 | 1337 |
| LMArena German | 1456 | 1340 |
| LMArena Japanese | 1405 | 1275 |
| LMArena Korean | 1416 | 1259 |
| LMArena Russian | 1457 | 1324 |
| LMArena Spanish | 1447 | 1346 |
Instruction Following Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 74.8 (#84), Mistral Small: 66.4 (#209)
| Benchmark | Grok 4.20 Multi-Agent | Mistral Small |
|---|---|---|
| LMArena Instruction Following | 1420 | 1310 |
| LiveBench Instruction Following | — | 63.7% |
Long Context Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.7 (#88), Mistral Small: 40.4 (#156)
| Benchmark | Grok 4.20 Multi-Agent | Mistral Small |
|---|---|---|
| LMArena Longer Query | 1431 | 1327 |
Writing & Preference Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 64.0 (#59), Mistral Small: 52.5 (#171)
| Benchmark | Grok 4.20 Multi-Agent | Mistral Small |
|---|---|---|
| LMArena Text | 1450 | 1338 |
| LMArena Creative Writing | 1436 | 1305 |
| LMArena Multi-Turn | 1452 | 1344 |
| LiveBench Language | — | 30.5% |
Frequently asked questions
Is Grok 4.20 Multi-Agent better than Mistral Small?
Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 33.4 on the Noometry Index. Mistral Small costs 6.0× less per token, which makes it the better buy when Grok 4.20 Multi-Agent's lead doesn't matter for your workload.
Which is cheaper, Grok 4.20 Multi-Agent or Mistral Small?
Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Grok 4.20 Multi-Agent lists at $1.25 and $2.50.
Is Grok 4.20 Multi-Agent or Mistral Small better for coding?
Grok 4.20 Multi-Agent scores higher on coding benchmarks: 43.0 versus 34.0 in the Noometry coding category.
Which has the bigger context window?
Grok 4.20 Multi-Agent does, with 1M tokens against 262K.
How many benchmarks do Grok 4.20 Multi-Agent and Mistral Small share?
18 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Mistral Small has 39.