Grok 3 Mini vs Llama 3.3 70B Instruct

Across our 12-test benchmark suite, Grok 3 Mini outright wins 4 categories, Llama 3.3 70B Instruct wins none, and the two tie on 8.

Tool Calling (5 vs 4): Grok 3 Mini scores 5/5, tied for 1st among 54 models with 16 others. Llama 3.3 70B Instruct scores 4/5, ranking 18th of 54. For agentic workflows, function routing, and multi-step API orchestration, this is a meaningful advantage — Grok 3 Mini's reasoning tokens (accessible via the include_reasoning parameter) likely contribute here.

Faithfulness (5 vs 4): Grok 3 Mini scores 5/5, tied for 1st of 55 models. Llama 3.3 70B Instruct scores 4/5, ranking 34th of 55. In RAG pipelines or document-grounded Q&A, a model that sticks to source material without hallucinating is critical — Grok 3 Mini's advantage here is operationally significant.

Persona Consistency (5 vs 3): The widest gap in this comparison. Grok 3 Mini scores 5/5, tied for 1st of 53 models. Llama 3.3 70B Instruct scores 3/5, ranking 45th of 53 — near the bottom. For chatbot personas, roleplay, or branded voice applications, this is a decisive edge for Grok 3 Mini.

Constrained Rewriting (4 vs 3): Grok 3 Mini scores 4/5, ranking 6th of 53. Llama 3.3 70B Instruct scores 3/5, ranking 31st of 53. Compression under hard character limits — ad copy, headlines, summaries — favors Grok 3 Mini.

Ties across 8 tests: Both models score identically on structured output (4/4), strategic analysis (3/3), creative problem solving (3/3), classification (4/4), long context (5/5), safety calibration (2/2), agentic planning (3/3), and multilingual (4/4). The tie on agentic planning at 3/5 (both ranking 42nd of 54) is worth flagging — neither model is strong here relative to the field.

External benchmarks (Epoch AI): Llama 3.3 70B Instruct has third-party math scores in our data: 41.6% on MATH Level 5 (ranking last, 14th of 14 models with this score) and 5.1% on AIME 2025 (ranking last, 23rd of 23). These place it at the bottom of the math-capable models we track. Grok 3 Mini has no external benchmark scores in the payload. The math scores for Llama 3.3 70B Instruct suggest it is not suited for competition-level or olympiad math tasks.

Grok 3 Mini costs $0.30/Mtok input and $0.50/Mtok output. Llama 3.3 70B Instruct costs $0.10/Mtok input and $0.32/Mtok output — 67% cheaper on input and 36% cheaper on output. In practice, at 1M output tokens/month, you pay $0.50 for Grok 3 Mini versus $0.32 for Llama 3.3 70B Instruct — a $0.18 difference that's negligible for most teams. Scale to 10M output tokens and the gap reaches $1,800/month; at 100M tokens it's $18,000/month. Developers running inference at scale — high-volume summarization pipelines, document processing, or content generation — should weigh that gap carefully against the quality wins Grok 3 Mini demonstrates. For occasional or moderate usage, the cost difference is unlikely to drive the decision.

Choose Grok 3 Mini if: you're building agentic systems that rely on accurate tool calling (5/5 in our tests), RAG pipelines where faithfulness to source material matters (5/5), customer-facing chatbots that must hold a persona (5/5 vs Llama's 3/5), or copywriting tools that need to hit strict character limits (4/5 vs 3/5). The reasoning token access via include_reasoning is a bonus for debugging and transparency. The cost premium — $0.50/Mtok output vs $0.32 — is worth it for these use cases.

Choose Llama 3.3 70B Instruct if: you're running high-volume workloads where the benchmarks that matter to you fall in the tied category (classification, long context, structured output, multilingual), and the 36% output cost savings compounds meaningfully at your scale. At 100M output tokens/month, that's $18,000 in savings. It also offers additional parameter controls — frequency_penalty, presence_penalty, repetition_penalty, min_p, top_k — that Grok 3 Mini does not, giving developers more fine-grained generation control. Avoid it for math-intensive tasks; its MATH Level 5 score of 41.6% and AIME 2025 score of 5.1% (both last-place among models tested, per Epoch AI) signal a real weakness there.