EuroLLM-9B-Instruct (2512) vs EuroLLM-22B-Instruct (2512)
parameter count at an identical 32768-token context window (9.15B vs 22.64B)
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Confronta modelli
Metti da due a quattro modelli a confronto sui campi che decidono un deployment: contesto, prezzo, regione, licenza, lingue, hosting e ciò che è verificato.
Editorially selected comparisons rather than every possible pair: 20.
EuroLLM-9B-Instruct (2512) vs EuroLLM-1.7B-Instruct
context window (32768 vs 4096 tokens)
EuroLLM-22B-Instruct (2512) vs EuroLLM-1.7B-Instruct
release date, the 2512 post-training generation against the 2024 checkpoint (2025-12-05 vs 2024-08-06)
OpenEuroLLM initial model release (planned) vs OpenEuroLLM final models (planned)
planned delivery date (31 December 2026 vs 31 January 2028)
EuroLLM-9B-Instruct (2512) vs OpenEuroLLM initial model release (planned)
weights downloadable against announced placeholder (open_weights true vs false)
EuroLLM-22B-Instruct (2512) vs OpenEuroLLM final models (planned)
licence recorded against unverified (apache-2.0 vs unknown)
Teuken 7B Instruct v0.6 vs EuroLLM-9B-Instruct (2512)
licence: CC-BY-NC-4.0, which forbids commercial serving, against Apache-2.0, which permits it
Pharia-1-LLM-7B-control-aligned vs EuroLLM-22B-Instruct (2512)
commercial channel: an on-premise agreement against publicly downloadable Apache-2.0 weights
Teuken 7B Instruct v0.6 vs Pharia-1-LLM-7B-control-aligned
EU21 average (0.57 project-reported against 0.417 in the OpenGPT-X evaluation)
Pharia-1-LLM-7B-control-aligned vs Pharia-1-Embedding-4608-control
output modality (text generation against embedding)
Devstral Small 2 (24B) vs Codestral 25.08
weights availability (downloadable Apache-2.0 checkpoint against API-only proprietary model)
Codestral 25.08 vs Qwen3-Coder-30B-A3B-Instruct
published parameter count (none published against 30.5B)
Devstral Small 2 (24B) vs GLM-4.7-Flash
published SWE-bench Verified score (68.0% against 59.2%, both vendor-reported)
Mistral Large 3 (675B) vs Mistral Small 4 (119B-A6B)
parameter count at an identical 262144-token context window (675B vs 119.4B)
Mistral Small 4 (119B-A6B) vs Ministral 3 8B
parameter count at an identical 262144-token context window (119.4B vs 8.92B)
Magistral Small 1.2 vs Devstral Small 2 (24B)
task specialisation at 24B: reasoning with explicit think tokens and vision input against agentic coding, text-only
Pixtral 12B vs Voxtral Small 24B
non-text input modality (vision against audio)
Mistral NeMo 12B Instruct vs Mistral 7B Instruct v0.3
context window (131072 vs 32768 tokens)
Mistral Small 4 (119B-A6B) vs EuroLLM-9B-Instruct (2512)
context window (262144 vs 32768 tokens)
Mistral Small 4 (119B-A6B) vs Gemma 4 31B IT
provider_slug (mistral against google), with the same Apache-2.0 licence and 262144-token context window
Dove due modelli differiscono, questa tabella mostra la differenza e si ferma. LLM EU non pubblica alcun badge di vincitore senza un punteggio documentato per quell'attività, e una cifra mancante rimane mancante invece di diventare zero.