Mistral Medium 3.5 128B vs GLM 5.3
At a Glance
| Compare |  Mistral Medium 3.5 128BMistral AI |  GLM 5.3Z.ai |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #16 of 4670.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 46.9–80.3 |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #34 of 44$0.248 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #26 of 3850.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 38.2–54.9 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $1.20Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $4.00Deepinfra ↗ · 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 | GLM-5.3 |
|---|---|---|
| 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 | 3.05100% of row best · score · GLM 5.3 (Max); 95% CI [2.43618871, 3.66634458]; sessions 73287; observations 6652488; rank 18 |
| 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 | 1,475.08100% of row best · rating · glm-5.3-max; 95% CI [1468.67816284, 1481.48915679]; votes 10960; rank 20 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 2 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 | GLM-5.3 |
|---|---|---|
| Developer | Mistral AI | Z.ai |
| Family | Mistral Medium 3 5 128b | Glm 5 3 |
| Model | Mistral-Medium-3.5-128B | GLM-5.3 |
| Version | Mistral-Medium-3.5-128B | GLM-5.3 |
| Lifecycle | active | active |
| Released | Unknown | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 262K | 1,000K |
| Total parameters | 127.7B | Unknown |
| Active parameters | Unknown | Unknown |
| License | other | Unknown |
| Open weights | Yes | No |
| API available | Unknown | Yes |
| Self-hostable | Yes | No |
| Provider access | Unknown | Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard) |
| Capabilities | chat, generation, reasoning, tools | agents, chat, reasoning, structured_outputs, tools |
Mistral Medium 3.5 128B Capabilities
GLM 5.3 Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
Mistral-Medium-3.5-128BMistral AI | vs | GLM-5.2Z.ai | cross-developer peerstext |
Mistral-Medium-3.5-128BMistral AI | vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text |
Claude Fable 5.1Anthropic | vs | Mistral-Medium-3.5-128BMistral AI | cross-developer peersimage, text |
 Gemini 3.1 ProGoogle DeepMind | vs | Mistral-Medium-3.5-128BMistral AI | cross-developer peerstext |
 DeepSeek-V4.1-FlashDeepSeek | vs | Mistral-Medium-3.5-128BMistral AI | cross-developer peersimage, text |
Mistral-Medium-3.5-128BMistral AI | vs | Grok 4.6xAI | cross-developer peersimage, text |
Mistral-Medium-3.5-128BMistral AI | vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text |
Mistral-Medium-3.5-128BMistral AI | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | Mistral-Medium-3.5-128BMistral AI | cross-developer peersimage, text |
Mistral-Medium-3.5-128BMistral AI | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | Mistral-Medium-3.5-128BMistral AI | cross-developer peersimage, text |
Mistral-Medium-3.5-128BMistral AI | vs | Mistral Large 3Mistral AI | family variantsimage, text |
Primary Evidence
Sources and Freshness
Questions
Mistral Medium 3.5 128B vs GLM 5.3 FAQs
Is Mistral Medium 3.5 128B or GLM 5.3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Mistral Medium 3.5 128B and GLM 5.3, 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 GLM 5.3?+
Only GLM 5.3 has a directly sourced input price: $1.20 per million tokens. Only GLM 5.3 has a directly sourced output price: $4.00 per million tokens.
Which has a larger context window, Mistral Medium 3.5 128B or GLM 5.3?+
GLM 5.3 has the larger sourced context window. Mistral Medium 3.5 128B supports 262K and GLM 5.3 supports 1,000K.
Which performs better in benchmarks, Mistral Medium 3.5 128B or GLM 5.3?+
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 GLM 5.3 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; GLM 5.3 is not marked open weight.
Can Mistral Medium 3.5 128B and GLM 5.3 understand images?+
Mistral Medium 3.5 128B is documented with image input; GLM 5.3 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Mistral Medium 3.5 128B or GLM 5.3?+
Neither has a larger sourced maximum output. Mistral Medium 3.5 128B is — and GLM 5.3 is 131K.
Do Mistral Medium 3.5 128B and GLM 5.3 support reasoning and tool use?+
Mistral Medium 3.5 128B: reasoning, tool calling, and image input. GLM 5.3: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Mistral Medium 3.5 128B or GLM 5.3?+
Mistral Medium 3.5 128B has 0 sourced provider routes; GLM 5.3 has 4, so GLM 5.3 has broader tracked availability.
Which offers better value, Mistral Medium 3.5 128B or GLM 5.3?+
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.