Mistral Medium 3.5 128B vs Qwen3.8 Max
At a Glance
| Compare |  Mistral Medium 3.5 128BMistral AI |  Qwen3.8 MaxQwen |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #10 of 4679.2 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 52.8–86.1 |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #23 of 44$0.107 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #6 of 3863.2 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 50.0–66.7 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $1.65Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $4.951Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 262K | 1,000K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 29, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Mistral-Medium-3.5-128B | Qwen3.8-Max |
|---|---|---|
| LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader | -10.8886% of row best · score · Mistral Medium 3.5; 95% CI [-12.33636331, -9.41760729]; sessions 10244; observations 358935; rank 43 | 3.30100% of row best · score · Qwen3.8 Max; 95% CI [2.46604139, 4.14181105]; sessions 31489; observations 2502655; rank 17 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,420.5896% of row best · rating · mistral-medium-3.5; 95% CI [1414.04225396, 1427.11615611]; votes 10996; rank 104 | 1,480.55100% of row best · rating · qwen3.8-max; 95% CI [1474.79040793, 1486.31846927]; votes 16670; rank 14 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader | 1,222.0593% of row best · rating · mistral-medium-3.5; 95% CI [1212.30064904, 1231.79518832]; votes 5090; rank 71 | 1,315.33100% of row best · rating · qwen3.8-max; 95% CI [1307.40892164, 1323.25970514]; votes 8665; rank 6 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 3 benchmark winsNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Mistral-Medium-3.5-128B | Qwen3.8-Max |
|---|---|---|
| Developer | Mistral AI | Qwen |
| Family | Mistral Medium 3 5 128b | Qwen3 8 Max |
| Model | Mistral-Medium-3.5-128B | Qwen3.8-Max |
| Version | Mistral-Medium-3.5-128B | Qwen3.8-Max |
| Lifecycle | active | active |
| Released | Unknown | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image, Video |
| Output modalities | Text | Text |
| Context window | 262K | 1,000K |
| Total parameters | 127.7B | 2.4T |
| Active parameters | Unknown | Unknown |
| License | other | Unknown |
| Open weights | Yes | No |
| API available | Unknown | Yes |
| Self-hostable | Yes | No |
| Provider access | Unknown | Alibaba Cloud Model Studio (Standard), Deepinfra (Standard), Fireworks Ai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | agents, chat, reasoning, structured_outputs, tools, vision |
Mistral Medium 3.5 128B Capabilities
Qwen3.8 Max Capabilities
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Mistral-Medium-3.5-128BMistral AI | vs | Mistral Large 3Mistral AI | family variantsimage, text |
| vs | Mistral-Medium-3.5-128BMistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Mistral Medium 3.5 128B vs Qwen3.8 Max FAQs
Is Mistral Medium 3.5 128B or Qwen3.8 Max better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Mistral Medium 3.5 128B and Qwen3.8 Max, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Mistral Medium 3.5 128B or Qwen3.8 Max?+
Only Qwen3.8 Max has a directly sourced input price: $1.65 per million tokens. Only Qwen3.8 Max has a directly sourced output price: $4.951 per million tokens.
Which has a larger context window, Mistral Medium 3.5 128B or Qwen3.8 Max?+
Qwen3.8 Max has the larger sourced context window. Mistral Medium 3.5 128B supports 262K and Qwen3.8 Max supports 1,000K.
Which performs better in benchmarks, Mistral Medium 3.5 128B or Qwen3.8 Max?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Mistral Medium 3.5 128B or Qwen3.8 Max be self-hosted?+
Mistral Medium 3.5 128B is the only model in this pair currently marked as self-hostable. Mistral Medium 3.5 128B is open weight; Qwen3.8 Max is not marked open weight.
Can Mistral Medium 3.5 128B and Qwen3.8 Max understand images?+
Mistral Medium 3.5 128B is documented with image input; Qwen3.8 Max is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Mistral Medium 3.5 128B or Qwen3.8 Max?+
Neither has a larger sourced maximum output. Mistral Medium 3.5 128B is — and Qwen3.8 Max is 131K.
Do Mistral Medium 3.5 128B and Qwen3.8 Max support reasoning and tool use?+
Mistral Medium 3.5 128B: reasoning, tool calling, and image input. Qwen3.8 Max: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Mistral Medium 3.5 128B or Qwen3.8 Max?+
Mistral Medium 3.5 128B has 0 sourced provider routes; Qwen3.8 Max has 4, so Qwen3.8 Max has broader tracked availability.
Which offers better value, Mistral Medium 3.5 128B or Qwen3.8 Max?+
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.