Granite 4.2 8B vs Llama 3.1 8B Instruct
Benchmark Performance
Available Benchmarks
| Benchmark | Granite 4.2 8B | Llama-3.1-8B-Instruct |
|---|---|---|
| LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader | 1,317.93100% of row best · rating · granite-4.2-8b; 95% CI [1306.62269586, 1329.24728966]; votes 3119; rank 219 | 1,186.3790% of row best · rating · llama-3.1-8b-instruct; 95% CI [1182.27083365, 1190.47005605]; votes 49605; rank 309 |
| Overall ResultCounted from the protocol-matched rows above | 1 benchmark winOverall lead | 0 benchmark wins |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Technical Differences
Side-by-Side Facts
| Field | Granite 4.2 8B | Llama-3.1-8B-Instruct |
|---|---|---|
| Developer | IBM | Meta |
| Family | Granite 4 2 | Llama 3 1 8b Instruct |
| Model | Granite 4.2 8B | Llama-3.1-8B-Instruct |
| Version | Granite 4.2 8B | Llama-3.1-8B-Instruct |
| Lifecycle | active | active |
| Released | 2026-08-25 | 2024-07-23 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
| Context window | 131K | 131K |
| Total parameters | 8.8B | 8B |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | llama3.1 |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Openrouter (Standard) | Hugging Face (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, tools |
16 comparable fields · 9 material differences · Pair passes the primary-source comparison gate
Granite 4.2 8B Capabilities
Llama 3.1 8B Instruct Capabilities
Internal Comparison Graph
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Primary Evidence
Sources and Freshness
Questions
Granite 4.2 8B vs Llama 3.1 8B Instruct FAQs
Is Granite 4.2 8B or Llama 3.1 8B Instruct better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Granite 4.2 8B and Llama 3.1 8B Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Granite 4.2 8B or Llama 3.1 8B Instruct?+
Granite 4.2 8B is $0.060 and Llama 3.1 8B Instruct is $0.050 per million tokens, so Llama 3.1 8B Instruct is cheaper on this metric. Granite 4.2 8B is $0.15 and Llama 3.1 8B Instruct is $0.080 per million tokens, so Llama 3.1 8B Instruct is cheaper on this metric.
Which has a larger context window, Granite 4.2 8B or Llama 3.1 8B Instruct?+
Neither model has a larger sourced context window in this comparison. Granite 4.2 8B is 131K and Llama 3.1 8B Instruct is 131K.
Which performs better in benchmarks, Granite 4.2 8B or Llama 3.1 8B Instruct?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Granite 4.2 8B or Llama 3.1 8B Instruct be self-hosted?+
Both models have the same recorded self-hosting status: supported. Granite 4.2 8B is open weight; Llama 3.1 8B Instruct is open weight.
Can Granite 4.2 8B and Llama 3.1 8B Instruct understand images?+
Granite 4.2 8B is not documented with image input; Llama 3.1 8B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Granite 4.2 8B or Llama 3.1 8B Instruct?+
Neither has a larger sourced maximum output. Granite 4.2 8B is — and Llama 3.1 8B Instruct is —.
Do Granite 4.2 8B and Llama 3.1 8B Instruct support reasoning and tool use?+
Granite 4.2 8B: reasoning and tool calling. Llama 3.1 8B Instruct: tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Granite 4.2 8B or Llama 3.1 8B Instruct?+
Granite 4.2 8B has 2 sourced provider routes; Llama 3.1 8B Instruct has 2, a tie.
Which offers better value, Granite 4.2 8B or Llama 3.1 8B Instruct?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.