Llama-4-Scout-17B-16E-Instruct vs Mistral-Medium-3.5-128B
Benchmark Performance
Available Benchmarks
| Benchmark | Llama-4-Scout-17B-16E-Instruct | Mistral-Medium-3.5-128B |
|---|---|---|
| LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader | 1,279.2590% of row best · rating · llama-4-scout-17b-16e-instruct; 95% CI [1274.53478136, 1283.95578792]; votes 29739; rank 255 | 1,421.16100% of row best · rating · mistral-medium-3.5; 95% CI [1414.62812191, 1427.69573067]; votes 11017; rank 98 |
| LMArena Vision Arenavision-2026-08-27-011508720696 · arena_rating · leader | 1,118.0891% of row best · rating · llama-4-scout-17b-16e-instruct; 95% CI [1108.62969338, 1127.52426769]; votes 6467; rank 110 | 1,222.18100% of row best · rating · mistral-medium-3.5; 95% CI [1212.39755732, 1231.95907443]; votes 5091; rank 67 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark wins | 2 benchmark winsOverall lead |
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 | Llama-4-Scout-17B-16E-Instruct | Mistral-Medium-3.5-128B |
|---|---|---|
| Developer | Meta | Mistral AI |
| Family | Llama 4 Scout 17b 16e Instruct | Mistral Medium 3 5 128b |
| Model | Llama-4-Scout-17B-16E-Instruct | Mistral-Medium-3.5-128B |
| Version | Llama-4-Scout-17B-16E-Instruct | Mistral-Medium-3.5-128B |
| Lifecycle | active | active |
| Released | 2025-04-05 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 10,000,000 | 262,144 |
| Total parameters | 108,641,793,536 | 127,704,210,176 |
| Active parameters | 17,000,000,000 | Unknown |
| License | other | other |
| Open weights | Yes | Yes |
| API available | Yes | Unknown |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Unknown |
| Capabilities | chat, generation, tools | chat, generation, reasoning, tools |
13 comparable fields · 7 material differences · Pair passes the primary-source comparison gate
Llama-4-Scout-17B-16E-Instruct Capabilities
Mistral-Medium-3.5-128B Capabilities
Internal Comparison Graph
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Primary Evidence
Sources and Freshness
Questions
Llama-4-Scout-17B-16E-Instruct vs Mistral-Medium-3.5-128B FAQs
Is Llama-4-Scout-17B-16E-Instruct or Mistral-Medium-3.5-128B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama-4-Scout-17B-16E-Instruct and Mistral-Medium-3.5-128B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Llama-4-Scout-17B-16E-Instruct or Mistral-Medium-3.5-128B?+
Only Llama-4-Scout-17B-16E-Instruct has a directly sourced input price: $0.10 per million tokens. Only Llama-4-Scout-17B-16E-Instruct has a directly sourced output price: $0.30 per million tokens.
Which has a larger context window, Llama-4-Scout-17B-16E-Instruct or Mistral-Medium-3.5-128B?+
Llama-4-Scout-17B-16E-Instruct has the larger sourced context window. Llama-4-Scout-17B-16E-Instruct supports 10,000,000 and Mistral-Medium-3.5-128B supports 262,144.
Which performs better in benchmarks, Llama-4-Scout-17B-16E-Instruct or Mistral-Medium-3.5-128B?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Llama-4-Scout-17B-16E-Instruct or Mistral-Medium-3.5-128B be self-hosted?+
Both models have the same recorded self-hosting status: supported. Llama-4-Scout-17B-16E-Instruct is open weight; Mistral-Medium-3.5-128B is open weight.
Can Llama-4-Scout-17B-16E-Instruct and Mistral-Medium-3.5-128B understand images?+
Llama-4-Scout-17B-16E-Instruct is documented with image input; Mistral-Medium-3.5-128B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Llama-4-Scout-17B-16E-Instruct or Mistral-Medium-3.5-128B?+
Neither has a larger sourced maximum output. Llama-4-Scout-17B-16E-Instruct is — and Mistral-Medium-3.5-128B is —.
Do Llama-4-Scout-17B-16E-Instruct and Mistral-Medium-3.5-128B support reasoning and tool use?+
Llama-4-Scout-17B-16E-Instruct: tool calling and image input. Mistral-Medium-3.5-128B: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Llama-4-Scout-17B-16E-Instruct or Mistral-Medium-3.5-128B?+
Llama-4-Scout-17B-16E-Instruct has 4 sourced provider routes; Mistral-Medium-3.5-128B has 0, so Llama-4-Scout-17B-16E-Instruct has broader tracked availability.
Which offers better value, Llama-4-Scout-17B-16E-Instruct or Mistral-Medium-3.5-128B?+
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.