WRPalmyra X5 Paid vs 
Mistral Medium 3.5 (batch) Open
Palmyra X5 vs Mistral Medium 3.5 (batch) compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$6 /M outputManaged API (no infra to run)
$3.75 /M outputNo per-token fees if you self-host
Palmyra X5 vs Mistral Medium 3.5 (batch) specs
| Spec | Palmyra X5 | Mistral Medium 3.5 (batch) | Winner |
|---|---|---|---|
| Maker | Writer | Mistral AI | – |
| Type | Proprietary | Open-weight | |
| Context window | 1M tokens | 262K tokens | WRPalmyra X5 |
| Input price | $0.6/M | $0.75/M · free self-host | WRPalmyra X5 |
| Output price | $6/M | $3.75/M · free self-host | |
| Vision / multimodal | No | Yes | |
| Tool / function calling | No | Yes | |
| Self-hostable | No (API only) | Yes | |
| License | Proprietary | Apache 2.0 |
Price gap & when to choose each
Mistral Medium 3.5 (batch) is ~1.6× cheaper than Palmyra X5 on output tokens ($3.75 vs $6 per M tokens).
- You want frontier performance through a managed API
- You need the longer 1M context window
- You value reliability & ecosystem
- You don't want to manage infrastructure
- You want to self-host or run on your cloud
- You prioritize data privacy & control
- You want the lowest operating costs
- You are building open or reproducible AI
Feature comparison
| Capability | Palmyra X5 | Mistral Medium 3.5 (batch) |
|---|---|---|
| Open weights (downloadable) | ✗ | ✓ |
| Self-hostable | ✗ | ✓ |
| Runs fully offline | ✗ | ✓ |
| Vision / multimodal | ✗ | ✓ |
| Tool / function calling | ✗ | ✓ |
| 1M+ context window | ✓ | ✗ |
Benchmarks: Palmyra X5 vs Mistral Medium 3.5 (batch)
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How Palmyra X5 and Mistral Medium 3.5 (batch) score
| Criterion | Palmyra X5 | Mistral Medium 3.5 (batch) |
|---|---|---|
| Cost-efficiency | 4.0 | 4.0 |
| Context window | 5.0 | 4.0 |
| Openness | 1.5 | 5.0 |
| Self-hosting | 1.0 | 5.0 |
| Multimodality | 2.0 | 5.0 |
Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.
What each model is
Palmyra X5 Paid
Palmyra X5 is Writer's most advanced model, purpose-built for building and scaling AI agents across the enterprise. It delivers industry-leading speed and efficiency on context windows up to 1 million...
Mistral Medium 3.5 (batch) Open
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex...
Other models in these families
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Frequently asked questions
Is Mistral Medium 3.5 (batch) as good as Palmyra X5?
Mistral Medium 3.5 (batch) is open-weight and competitive on many tasks, but Palmyra X5 may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.
Can I run Mistral Medium 3.5 (batch) locally?
Yes. Mistral Medium 3.5 (batch) has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Palmyra X5 is API-only and cannot be self-hosted.
How much cheaper is Mistral Medium 3.5 (batch)?
Mistral Medium 3.5 (batch) costs $3.75/M output vs $6/M for Palmyra X5 — roughly 2x cheaper via API, and free if you self-host.
Palmyra X5 vs Mistral Medium 3.5 (batch) — which should I pick in 2026?
Choose Mistral Medium 3.5 (batch) if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Palmyra X5 if you want frontier capability through a managed API with zero infrastructure to run.
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