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Granite 4.1 8B vs Llama 3.3 70B Instruct

Detailed technical comparison between Granite 4.1 8B (IBM) and Llama 3.3 70B Instruct (Meta). Review live API token pricing, context window capabilities, time-to-first-token latency, and verified benchmark scores side-by-side.

⚡ Executive Summary & Verdict

Comparison Snapshot

Granite 4.1 8B: 0 WinsvsLlama 3.3 70B Instruct: 6 Wins
Context Leader

Tie

Equal Capacity
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

Granite 4.1 8B

$0.05 / MTok
IBMactive

Granite 4.1 8B

Granite 4.1 8B is a dense, decoder-only 8-billion-parameter language model from IBM, part of the Granite 4.1 family. It supports a 131K-token context window and is designed for enterprise tasks...

View Granite 4.1 8B Full Specs →
Metaactive

Llama 3.3 70B Instruct

Meta's state-of-the-art open weights model, providing enterprise-grade reasoning and logic. Exceptionally powerful for self-hosted customer support, text generation, and tooling workflows.

View Llama 3.3 70B Instruct Full Specs →

Technical Specifications

🏆 = Superior Spec
SpecificationGranite 4.1 8BLlama 3.3 70B Instruct
ProviderIBMMeta
Context Window131,072 tokens131,072 tokens
Agent SuitabilityNot yet benchmarked83/100 (est.)
Time to First Token (TTFT)No public TTFT data280 ms (est.)
Deployment Modelmanaged apiself hostable
Production StabilityStable GA (est.)Stable GA (est.)
API AvailableYesYes
Released Date2026-04-302024-12-06

API Pricing Comparison

Input Price per Million Tokens

Granite 4.1 8B

$0.05

Llama 3.3 70B Instruct

$0.13

Output Price per Million Tokens

Granite 4.1 8B

$0.10

Llama 3.3 70B Instruct

$0.40

💡 Cost Ratio: Granite 4.1 8B is 2.6x cheaper per input token than Llama 3.3 70B Instruct.

Want to test both models live?

Run side-by-side prompt benchmarks in our dynamic multi-model Sandbox. Compare execution speeds, latency metrics, and compute actual costs in real-time.

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Benchmark Performance Metrics

Standardized Scores (0–100%)

Scores show verified raw accuracy percentages across standardized AI evaluation suites. Higher bars indicate superior performance in that domain.

MMLUGeneral knowledge & multi-task understanding
75.4%vs86.2%+10.8% Llama 3.3 70B Instruct
Granite 4.1 8B
Llama 3.3 70B Instruct 🏆
HumanEvalPython coding & logic synthesis
71.6%vs88.0%+16.4% Llama 3.3 70B Instruct
Granite 4.1 8B
Llama 3.3 70B Instruct 🏆
MATHComplex mathematical problem solving
41.4%vs75.0%+33.6% Llama 3.3 70B Instruct
Granite 4.1 8B
Llama 3.3 70B Instruct 🏆
GPQAGraduate-level expert reasoning
28.8%vs52.0%+23.2% Llama 3.3 70B Instruct
Granite 4.1 8B
Llama 3.3 70B Instruct 🏆
HellaSwagCommonsense reasoning and inference
76.0%vs88.5%+12.5% Llama 3.3 70B Instruct
Granite 4.1 8B
Llama 3.3 70B Instruct 🏆
MT-BenchMulti-turn conversation flow quality
7.9%vs8.8%+0.9% Llama 3.3 70B Instruct
Granite 4.1 8B
Llama 3.3 70B Instruct 🏆

Granite 4.1 8B Quirks & Gotchas

No developer gotchas reported.

Llama 3.3 70B Instruct Quirks & Gotchas

  • ▸Stable, well-documented self-hosted option with strong community support
  • ▸Outperformed by Llama 4 Maverick for agentic tool-calling workflows

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